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Every helpdesk vendor now sells "AI". What they actually ship differs a lot. Some offer a chatbot that answers customers before a ticket exists. Some offer a copilot that drafts replies for agents. Others hand you a platform and a consultant's invoice. The pricing models differ too: per seat, per conversation, per "resolution", or a pool of credits that nobody on the buying committee fully understands. We looked at six options, from a free do-it-yourself build to a full enterprise ITSM suite. Each one gets the same treatment: what it does well, where it falls short, and what it costs as of September 2026. Disclosure: this review is published on Jitbit's blog, and Jitbit is one of the products below. We tried to hold it to the same standard as the others, and we list its weaknesses too. Competitor prices come from public pricing pages and recent third-party breakdowns. Vendors change prices often, so check before you sign. How we evaluated Grounding. Does the AI answer from your documentation and ticket history, or from general model knowledge? Coverage. Does it deflect tickets (customer-facing), help agents (agent-facing), or both? Cost predictability. Can you forecast next quarter's bill without a spreadsheet model? Time to value. Days, weeks, or a multi-month implementation project? 1. Homegrown & Free: a Copilot Studio agent grounded on SharePoint Best for: internal IT support in organizations that already run on Microsoft 365. This option gets overlooked because nobody sells it. If your company already lives in Microsoft 365, you can build a decent self-service IT assistant in an afternoon without buying a helpdesk. The recipe is simple: put your end-user documentation on one SharePoint site, point a Copilot Studio agent at it, and publish the agent to Teams, where your employees already spend the day. Here is how to do it well. How to set it up Create a dedicated SharePoint communication site, for example "IT Help". Keep the knowledge the agent will use on this one site, not scattered across team sites. A single, clean source gives better answers than a large, messy one. Write one page per problem. "Reset your VPN token", "Printer on floor 3 shows offline", "Request a new laptop". Use the error message or symptom a user would type as the page title, and put the fix in numbered steps. Retrieval works on chunks of text, so short focused pages beat a 60-page PDF manual. Avoid scanned PDFs and screenshots-only pages, because the agent cannot read text inside images reliably. Check permissions. The agent answers using the identity of the person asking, so it only sees what that person can see in SharePoint. Give all employees read access to the site. Keep admin-only runbooks on a separate site so they never leak into employee answers. Create the agent in Copilot Studio (copilotstudio.microsoft.com). Add the SharePoint site URL as a knowledge source, and keep authentication set to "Authenticate with Microsoft", which SharePoint knowledge requires. Turn off general knowledge. In the agent's generative AI settings, disable the option that lets the model answer from its own general knowledge. You want "I don't know" rather than a confident, invented fix for your internal VPN. Write short instructions. For example: "You are the IT help assistant for Contoso employees. Answer only from the IT Help site. Give numbered steps. If the answer is not in the documentation, say so and link to the ticket form." Add an escalation path. Change the fallback topic so unanswered questions end with a link to your ticket form or IT mailbox. More advanced teams add an agent flow that opens a ticket directly, but each tool call uses extra credits. Publish to Teams and Microsoft 365 Copilot, then pin the agent in Teams for all employees through the Teams admin center. If people have to look for the agent, adoption stays low. Review analytics every week. Copilot Studio shows which questions went unanswered. Each one is a missing SharePoint page. Write it, and the agent improves by the next morning. This loop matters more than anything else on this list. Pros. There is no new vendor, no procurement cycle, and no new login. Employees ask questions in Teams, where they already are. Identity, permissions and compliance come from your existing Microsoft tenant, so security review is short. The knowledge base is ordinary SharePoint pages that anyone in IT can edit, with no proprietary format to migrate later. For the large share of internal tickets that are really "how do I..." questions (password resets, VPN, printers, Wi-Fi, software requests), a well-written site plus a grounded agent can deflect a meaningful share of volume in the first month. Cons. This is a self-service answer engine, not a helpdesk. There is no ticket queue, no SLA tracking, no assignment, no reporting on agent workload, and no audit trail of who fixed what. When the bot can't help, the issue goes to email or a form, and you still need something to manage it. Answer quality depends entirely on the documentation. A thin or outdated SharePoint site produces thin or outdated answers. Copilot Studio's credit-based licensing is also hard to forecast, and agents can be disabled automatically once a tenant goes 25% over its prepaid capacity. It works for employees only. Do not try to turn it into a customer-facing support bot. Price. Effectively free if your users already have Microsoft 365 Copilot licenses. Microsoft does not charge credits when licensed users talk to employee-facing agents, within fair-use limits. Without those licenses, Copilot Studio bills in credits: $200 per month for a pack of 25,000, or $0.01 per credit pay-as-you-go through Azure. A generative answer grounded on a knowledge source costs 2 credits. With the optional tenant-graph grounding it costs 12. In practice, that is roughly two to twelve cents per answer, and a few hundred dollars a month covers a mid-sized company's internal IT questions. The real cost is the staff time to write and maintain the SharePoint pages. You would need that documentation with any tool on this list anyway. 2. Jitbit Helpdesk Best for: mid-sized support and IT teams that want a full ticketing system with AI included, not billed separately. Pros. AI is built into the ticketing workflow, not added as a separate product. An AI assistant panel in every ticket drafts replies grounded on your knowledge base, indexed external documentation, canned responses, and similar closed tickets. It also summarizes long threads, cleans up agent drafts, and turns solved tickets into new KB articles, which helps teams that are just starting a knowledge base. Automation rules can run AI triage on every incoming ticket (sentiment, category and priority in one pass) and can post first-line AI replies either directly to the customer or as internal notes for review. The live chat widget has an AI auto-responder that hands off to a human when the visitor asks for one. For technical teams, the AI can call your own HTTP endpoints or MCP servers, so it can look up an order status or a subscription without an agent. Model choice is unusually open: GPT and Gemini are included, or you can bring your own key for Claude, Azure OpenAI or AWS Bedrock. That matters for data-residency and HIPAA reviews, and Jitbit signs a BAA on its Enterprise plan. It is also one of the few products here that still offers a self-hosted, on-premise edition with the same AI features. Cons. Jitbit is a smaller vendor, and its integration marketplace is much smaller than Freshdesk's or ServiceNow's. Its customer-facing bot is a helpful extra on top of a helpdesk, not a dedicated conversational platform. Teams with very high chat volume in B2C, which is Fin's specialty, will find fewer controls for multi-step procedures and channel orchestration. Like every grounded AI, it only performs as well as the knowledge base behind it. On-premise customers who want semantic search and document indexing must run an extra Docker-based add-on, and they supply their own model API keys. The entry-level Freelancer plan does not include AI credits. Price. Flat plans with no per-resolution or per-session fees: Freelancer $29/month (1 agent), Startup $69/month (4 agents), Company $129/month (7 agents), Enterprise $249/month (9 agents, $29 per extra agent). Annual billing saves about two months. Unlimited AI credits are included from the Startup plan up. For a seven-agent team, that works out to about $18 per agent per month with AI included. On most of the other paid products here, AI alone costs more than that per agent. 3. Fin (by Intercom) Best for: high-volume customer-facing support where deflection rate is the main metric. Pros. Fin is arguably the most capable customer-facing AI agent on the market, and it is the product the rest of the category measures itself against. It handles multi-turn conversations well, follows written "procedures" for multi-step tasks such as refunds or account changes, and works across chat, email, and voice. Importantly, Fin does not require Intercom's helpdesk. It can run on top of Zendesk, Salesforce, Freshdesk, Front, and others, so you can add it to an existing stack without migrating. Its reporting is built around resolution rate, which makes the ROI case easy to present to a CFO. Cons. Outcome-based pricing is fair in theory and hard to budget in practice. Fin counts an "assumed resolution" when a customer simply stops replying after its last answer. That includes customers who gave up. Your bill grows with volume, not with headcount, so a seasonal spike or a product incident that floods support also increases your AI spend. Fin is built for customer-facing deflection. Agent-side features are stronger inside Intercom's own inbox, so standalone deployments on other helpdesks get less of the product. For internal IT support, it is the wrong tool. Price. $0.99 per billable outcome (a resolution, a procedure handoff or a disqualification), and $9.99 per qualified sales lead. Running standalone on another helpdesk has a minimum of 50 outcomes a month. Inside Intercom, you also pay for seats: Essential $29, Advanced $85, or Expert $132 per seat per month on annual billing. A ten-seat Advanced team resolving 2,000 conversations a month pays roughly $2,800, and about 70% of that is Fin. 4. Tidio (with Lyro AI) Best for: small e-commerce stores that mainly need a website chatbot. Pros. Tidio is one of the fastest ways to get an AI chatbot onto a website. Lyro, its AI agent, learns from your FAQ and site content in minutes, and setup takes almost no technical skill. It integrates well with Shopify, WordPress, and the common e-commerce stack, so it can answer order and shipping questions that make up most of a small shop's inbox. The visual Flows builder handles cart-abandonment nudges and lead capture alongside support. For a one- or two-person store, the free tier is enough to try it before paying. Cons. Tidio is chat-first, and the ticketing side is basic. There is little in the way of SLAs, complex routing, asset management, or the reporting a growing support or IT team eventually needs. Lyro is billed by conversation, and the free and Starter plans include only 50 Lyro conversations in total, not per month. After that, it stops answering. The plan structure has a big gap: the jump from Growth to Plus is more than tenfold, with no middle tier. Teams often report that real costs run two to three times the advertised price once AI and Flows add-ons are included. It is not designed for B2B, internal IT, or regulated industries. Price. Starter $29/month, Growth from $59/month (scaling to about $349 depending on volume), Plus $749/month, and Premium from $2,999/month. Lyro AI is a separate add-on starting at $39/month, and Flows costs another $29/month. A typical Growth setup with Lyro and Flows costs around $127/month before overages. Annual billing saves about 17%. 5. Freshdesk (with Freddy AI) Best for: mid-market customer support teams that want a mainstream, feature-complete suite and can live with add-on pricing. Pros. Freshdesk is a mature, full-featured helpdesk with omnichannel support, a large app marketplace, solid automation, and a familiar interface that new agents learn quickly. Freddy AI covers both sides of the job. The Freddy AI Agent deflects questions on chat, email and the web widget. Freddy Copilot helps human agents with reply drafts, summaries, tone adjustment and suggested solutions. Freshworks also sells Freshservice for internal IT, so organizations can standardize on one vendor for both customer and employee support. Cons. AI costs are split across several meters and plan requirements. Copilot is available only on Pro and Enterprise, so Growth customers cannot buy it at any price. The customer-facing AI Agent is billed by session, and unused sessions expire at the end of each billing cycle instead of rolling over. Freshworks raised plan prices in 2026 for the first time in five years and cut the free plan to a six-month program for one or two agents. Model choice and on-premise deployment are not available. Price. Growth $19, Pro $55, Enterprise $89 per agent per month (annual billing). Freddy Copilot adds $29 per agent per month ($35 on monthly billing). The AI Agent includes 500 sessions, then costs $49 per 100 sessions. The realistic entry point for agent-side AI is $84 per agent per month (Pro plus Copilot). A five-agent team on Pro with Copilot and moderate bot usage spends roughly $650-700 a month. 6. ServiceNow (with Now Assist) Best for: large enterprises running IT, HR and facilities service management on one platform. Pros. ServiceNow is the default choice for enterprise ITSM, and its AI benefits from being close to all of that data. Now Assist summarizes incidents, drafts resolution notes, generates KB articles from resolved cases, and powers a Virtual Agent that can complete requests end to end instead of just answering questions. Because it sits on the same platform as the CMDB, change management, and HR and facilities workflows, the AI can act on real records: reset an account, provision software, or open a change request. No other product here offers that level of process depth, governance, and audit trail. In 2026 ServiceNow moved to AI-native tiers, so AI is now included by default rather than sold as a separate SKU. Cons. Cost and complexity. Implementations usually take months and a certified partner, and the platform typically needs dedicated administrators after go-live. Pricing is quote-only and heavily negotiated, so two companies of the same size can pay very different amounts. AI usage now draws from consumption-based "Assist" pools, which adds another capacity figure to forecast and renegotiate. For organizations under about a thousand employees, ServiceNow is usually more platform than they need. Price. There is no public price list. In April 2026, ServiceNow replaced its Standard/Pro/Pro Plus/Enterprise tiers with Foundation, Advanced and Prime, and older SKUs reached end of sale in mid-2026. As a reference point, legacy ITSM Pro licenses were widely reported at around $100-135 per fulfiller per month. Adding Now Assist (Pro Plus) raised that by an estimated 50-60%, to roughly $200-215 per fulfiller per month. Minimum seat commitments, platform fees and implementation services often make the first-year total a six-figure amount. Side-by-side Solution Best fit Pricing model AI included? Copilot Studio + SharePoint Internal IT, Microsoft shops Credits, or free with M365 Copilot licenses Yes (it's only AI, no ticketing) Jitbit SMB and mid-market support and IT Flat monthly plans Yes, unlimited from Startup plan Fin High-volume customer support $0.99 per outcome, plus seats in Intercom It is the product Tidio Small e-commerce Plan plus Lyro conversation add-on Add-on from $39/month Freshdesk Mid-market customer support Per agent, plus Copilot seats and bot sessions Add-on, $29/agent plus sessions ServiceNow Large-enterprise ITSM Quote-only, per fulfiller, plus Assist pools Bundled in 2026 tiers The bottom line Start with the question you're really trying to answer. If you want employees to stop emailing IT about VPN passwords and you already pay Microsoft, build the SharePoint and Copilot Studio agent first. It costs almost nothing, and the documentation you write for it will make any helpdesk you buy later work better. If you need an actual ticketing system with AI included and a predictable bill, Jitbit and Freshdesk are the main choices, and they differ mostly in how AI is charged. If deflecting a large volume of customer chats is the whole goal, Fin sets the standard, as long as you are comfortable with a bill that grows with volume. Tidio fits small online stores. ServiceNow fits organizations large enough to need a service-management platform, with a budget to match. Whatever you choose, AI quality comes from your knowledge base, not the model. Every product here gives better answers with better documentation, so start writing it now.
Our new Microsoft Teams app just passed Microsoft's certification and is live in the Teams Store: Jitbit Helpdesk Bot. Search "Jitbit" in the Teams app store and it's right there - no custom app uploads, no admin-center gymnastics. Unlike our old webhook integration (one-way channel notifications, now deprecated), this is a proper two-way bot: End users create tickets in chat - type new and get a real form with category and priority, or turn any Teams message into a ticket from the "..." message menu. my tickets lists your open requests Technician replies come back to Teams - as cards with an inline answer box, so the whole conversation can happen without opening the helpdesk Channels get actionable ticket cards - @mention the bot, type subscribe, and every new ticket shows up with Take it / Reply / Close buttons. Cards update in place when the ticket changes - whether that happens in Teams or in the web app Setup takes about two minutes: install the app, click "Generate pairing command" on the helpdesk admin page, paste the command into a chat with the bot. Users are matched by their Microsoft 365 email automatically. Self-hosted customers run their own private bot, so ticket traffic never touches our servers. The bot is included with all plans. Details and setup steps: the integration page and the documentation.
Help desk interviews usually test two things at once: whether you understand the technical basics, and whether you can explain those basics to a person who may already be annoyed, confused, or late for a meeting. That combination matters. A support technician who can diagnose a network issue but makes the user feel stupid will struggle. So will a friendly person who guesses randomly at technical problems. The best candidates show both: methodical troubleshooting and calm, useful communication. Below are common help desk and desktop support interview questions, with sample answers you can adapt to your own experience. Technical Help Desk Interview Questions 1. Can you tell me about yourself? Keep the answer focused on the job. Mention your IT training, support experience, certifications, customer service background, and the kind of technical problems you have handled. Avoid turning it into a life story. A good answer gives the interviewer several useful follow-up paths. For example: "I have been building my support skills through Windows troubleshooting, networking fundamentals, and customer-facing work. I enjoy breaking problems down, documenting what I find, and helping users get back to work without making the process more stressful for them." 2. A user says their monitor is not working. What do you check first? Start with the simple physical checks before assuming a complicated failure. Confirm that the monitor has power, the brightness is not turned all the way down, the video cable is connected securely, and the computer itself is powered on. If the monitor has multiple inputs, make sure the correct input is selected. If those checks do not solve it, continue with another cable, another monitor, or another port. From there, you can investigate graphics drivers, docking stations, sleep state problems, or hardware failure. 3. What is Safe Mode used for? Safe Mode starts Windows with a limited set of drivers and services. It is useful when a normal startup fails, when a bad driver causes crashes, or when you need to remove unwanted software that loads during a standard boot. The exact steps depend on the Windows version, but the general idea is to restart into the recovery or advanced startup options and choose Safe Mode or Safe Mode with Networking. 4. What is an IP address? An IP address identifies a device on a network so other devices know where to send traffic. On a typical office network, a computer may receive its IP address automatically from DHCP, although servers, printers, and network equipment often use fixed addresses. On Windows, you can check the assigned address with ipconfig or ipconfig /all in Command Prompt. You can also find it in the network adapter settings. 5. What is a default gateway? A default gateway is the device a computer uses when it needs to reach something outside its local network. In many offices and homes, that gateway is a router or firewall. Without a working gateway, a computer may still talk to nearby devices but fail to reach the internet or other remote networks. 6. What is Active Directory? Active Directory is Microsoft's directory service for managing users, computers, groups, permissions, and policies in a Windows domain environment. In practical help desk work, you may use it to reset passwords, unlock accounts, check group membership, or confirm which computers belong to the domain. 7. What is a windows domain? A domain is a centrally managed group of users, computers, and resources. Instead of each PC having completely separate local accounts and permissions, a domain lets administrators manage access from one place, usually through Active Directory. For help desk work, this matters because a user's ability to sign in, access file shares, use printers, or launch certain applications may depend on their domain account and group memberships. 8. A printer is printing strange symbols or garbled pages. What might cause that? A common cause is the wrong printer driver or a corrupted print job. I would first clear the print queue, confirm the correct printer model and driver, and reinstall or update the driver if needed. I would also check whether other users are affected, because that helps determine whether the issue is local to one workstation or shared across the printer or print server. 9. What are common Ethernet cable categories? Common twisted-pair Ethernet cable categories include Cat5e, Cat6, and Cat6a. Cat5e is widely used for gigabit networking, Cat6 is also common for gigabit and shorter 10 GbE runs, and Cat6a is designed for 10 GbE over longer distances. In an interview, it is usually enough to show that you understand the categories affect supported speed, distance, and installation quality. 10. What is a blue screen? A blue screen, often called a BSOD, is a Windows stop error. It can be caused by failing hardware, bad drivers, memory problems, disk issues, overheating, or low-level software conflicts. A sensible troubleshooting path is to note the stop code, check recent changes, review Event Viewer, update or roll back drivers, run hardware diagnostics, test memory, and look for patterns such as crashes only after docking, printing, or launching a specific application. 11. What does DHCP do? DHCP stands for Dynamic Host Configuration Protocol. It automatically gives network settings to devices, including IP address, subnet mask, default gateway, and DNS servers. Without DHCP, users or administrators would have to configure those values manually on each machine. 12. What does DNS do? DNS translates names people can read into IP addresses computers can use. For example, when someone visits a website, DNS helps find the server behind that domain name. In support work, DNS problems can look like "the internet is down" even when the network connection itself is working. Useful checks include trying another site, using nslookup, checking the DNS server address, and flushing the local DNS cache when appropriate. 13. What is a VPN? A VPN creates an encrypted connection from a user's device to a private network. Remote employees often use VPNs to access internal applications, file shares, intranet sites, or administrative systems that are not exposed to the public internet. When troubleshooting VPN issues, check credentials, MFA prompts, internet connectivity, client version, certificate problems, and whether the user is on a restricted network. 14. What is the ping command used for? ping sends test packets to another host and reports whether replies come back. It is a quick way to check basic reachability and latency. It does not prove that a website, file share, or application is working, but it can help narrow down whether a device can reach another device at all. 15. What is Group Policy? Group Policy is a Windows feature used to apply settings across users and computers in a domain. Administrators can use it to configure password rules, mapped drives, desktop restrictions, security settings, software deployment, browser settings, and many other policies. For a help desk technician, Group Policy is often relevant when a user cannot access a feature that someone else can, or when settings keep changing back after a reboot or login. 16. What is a PST file? A PST file is an Outlook data file, commonly used to store email, calendar items, contacts, and archives locally. In support scenarios, PST files come up during Outlook migrations, archive recovery, mailbox troubleshooting, and storage cleanup. 17. How would you change folder permissions? First, confirm who should have access and whether the folder is local, on a file server, or controlled by a broader policy. On Windows, folder permissions are usually managed from the Security tab in the folder properties, where an administrator can add users or groups and assign permissions such as Read, Modify, or Full Control. In a company environment, it is usually better to grant access through security groups rather than adding individual users one by one. 18. What is the difference between a hub and a switch? A hub sends traffic out to every connected device, whether the traffic is meant for that device or not. A switch is smarter: it learns which devices are connected to which ports and forwards traffic only where it needs to go. That makes switches much more efficient and secure for modern networks. Hubs are mostly obsolete, but interviewers still ask the question because it tests basic networking knowledge. 19. How would you recover files from a virus-infected computer? Do not rush to copy files from an infected machine onto the network. First isolate the computer, document symptoms, and follow company security procedure. If recovery is approved, use a clean, trusted environment and scan the drive with updated security tools before moving any files. Depending on the incident, the correct answer may involve escalating to security, preserving evidence, or restoring from a known-good backup rather than manually extracting files. 20. Why should we hire you? Use this answer to connect your skills to the role. Mention technical fundamentals, reliability, communication, willingness to learn, and any experience that proves you can handle real users under real pressure. A strong answer is specific: "You should hire me because I can troubleshoot methodically, explain technical issues clearly, and stay patient when users are stressed. I also document my work, ask for help before wasting time, and keep learning so I can solve more problems independently." Customer Service Help Desk Interview Questions Technical answers matter, but help desk work is still service work. Interviewers want to know how you behave when the problem is unclear, the user is frustrated, or the ticket queue is already full. 1. What makes someone good at help desk work? A good help desk employee listens carefully, asks clear questions, and explains the next steps without drowning the user in jargon. They also know when to keep troubleshooting and when to escalate. Speed matters, but accuracy, documentation, and the user's experience matter too. 2. What do you do when you cannot solve an issue? I would gather the important details first: what changed, who is affected, what error appears, what has already been tried, and how urgent the issue is. If I still cannot resolve it, I would escalate with clean notes so the next person does not have to start from zero. 3. How do you handle an angry or frustrated user? Stay calm and avoid arguing. Let the user explain the problem, acknowledge the impact, and move the conversation toward the next useful action. A simple sentence like "I can see why that is frustrating; let's check the fastest things first" can lower the temperature without making unrealistic promises. 4. Tell me about a conflict you had and how you resolved it. Choose an example where you stayed professional and solved the actual issue. The best answers are not dramatic. A misunderstanding about priority, a handoff problem, or a disagreement about procedure can work well if you explain what you learned and how you prevented it from happening again. 5. How would you rate your troubleshooting ability? Be confident but realistic. If you are early in your career, a four out of five is often more believable than claiming perfection. Explain that you are strong at structured troubleshooting, documentation, and asking good questions, while still knowing when to escalate unfamiliar problems. 6. How do you keep your IT knowledge current? Mention specific habits: reading vendor documentation, practicing in a lab, following release notes, taking courses, studying for certifications, or learning from tickets after they are resolved. Interviewers like answers that show steady curiosity rather than vague "I read online" statements. 7. Why do you want to work in help desk? A good answer connects problem-solving with service. You might say that you enjoy figuring out technical issues, helping people get unstuck, and learning a wide range of systems. Help desk roles expose you to many parts of IT, which makes them a strong starting point for a support career. 8. How do you stay organized? Talk about your system. For example, you might prioritize tickets by urgency and impact, keep notes inside the ticket, use reminders for follow-ups, and close the loop with users before marking work complete. The point is to show that you do not rely on memory alone. 9. Is teamwork important in help desk? Yes. Support teams depend on clean handoffs, shared knowledge, and good escalation notes. No one knows every system, and many incidents require cooperation between help desk, infrastructure, security, vendors, and department managers. 10. Which ticketing systems have you used? If you have used a ticketing system before, name it and describe what you did with it: creating tickets, assigning priorities, documenting work, escalating issues, using canned responses, or building a small knowledge base. If you have not used one professionally, say so honestly, then explain that you understand the core workflow: capture the request, categorize it, prioritize it, document progress, communicate updates, and close the ticket when the user confirms the issue is resolved. Final Tips Before the Interview Practice explaining technical ideas in plain language. Prepare a few real examples from school, work, home labs, or previous customer service jobs. Do not pretend to know something you do not know. Explain how you would find out. When answering troubleshooting questions, start simple and move step by step. Show that you care about documentation, follow-up, and the user's experience. The strongest help desk candidates do not sound like they memorized a script. They sound like people who can stay calm, think clearly, and keep a user informed while working through the problem.
Short version: every AI feature we ship on the hosted helpdesk now runs on the self-hosted edition too. It's a separately licensed Docker add-on, perpetual license, one-time payment. Customer data stays on your network. Requires Jitbit Helpdesk v11.22 or newer. Why this took a while Our AI stack isn't a thin wrapper around an LLM API. It's a Python service running a local vector database (Qdrant), embedding models, and a RAG pipeline tuned against support-desk content. That's what makes "similar KB articles" surface the right article, and what keeps reply drafts grounded in your own documentation instead of hallucinated. Running that stack on our own hosting is one thing. Packaging it so your IT team can stand it up on your own hardware without babysitting Python dependencies is another. We sat on it until we had something we'd be comfortable supporting. What you get Similar-article suggestions inside tickets - ranked by semantic similarity, not keyword overlap Semantic KB search for end-users - results ranked by meaning AI-generated reply drafts grounded in your KB, writing-style rules, and the ticket context External documentation indexing - crawl your own docs, wiki, or any internal site and use it as AI context alongside the KB Choice of embedding model - free local model that runs on CPU, or OpenAI embeddings with your own key Generative provider - OpenAI, Azure OpenAI, or AWS Bedrock, customer brings their own key Feature parity with SaaS. No caveats about "basic" ChatGPT integration. How it ships A Docker Compose stack you drop in next to your existing Helpdesk install. Runs on Windows or Linux, bare metal or VM, Intel/AMD or ARM. Upgrades are zero-downtime and preserve Docker volumes — indexed data and cached models carry over. Full setup and system requirements are in the manual. Privacy This is the reason we finally built this. With the bundled local embedding model, nothing about your tickets, KB articles, or indexed documentation leaves your network. No embeddings sent to OpenAI. No vectors stored in a third-party service. The vector DB is a container on a host you own. If you want a generative model for reply drafts, you bring your own API key. Azure OpenAI and AWS Bedrock keep everything inside your existing cloud tenancy, with a BAA if you need one. For regulated on-prem buyers — healthcare, defense, financial services, government — this was the #1 reason you told us you couldn't adopt our AI features. It's no longer a reason. Pricing Licensed separately from the core Helpdesk product. Perpetual license, one-time payment, 1 year of updates included - same model as the rest of the on-prem lineup. No subscription, no per-agent add-on, no per-request fees. See the pricing page for the current price, and the on-prem AI landing page for the full feature list and requirements. Setup instructions live at jitbit.com/docs/ai-on-premise.
Do we even need helpdesk software? I mean, just give an AI agent a markdown skill file with your FAQ and canned responses and let it answer tickets - right? I (obviously) gave it a lot of thought recently and here's my take: If your entire support operation is one person answering the same three questions, congratulations, you've solved customer service. Ship it. For everyone else operating in reality - helpdesk apps do not automate support. They automate the messy human stuff around it. Workflow state & accountability Support isn't just answering questions - it's tracking who's answering them, who dropped the ball, and whose turn it is to care. Who owns this ticket? What's the SLA status? Did the second-line team even look at it, or did it rot in a queue for three days while everyone assumed someone else was on it? Teams need audit trails, escalation chains, and - let's be honest - blame-able history. An AI agent can triage, prioritize, categorize, and even draft a lovely response. It cannot enforce a process across a 70-person org where half the team is in a different timezone and the other half is "working from home" (AKA "at the beach"). Nobody's ripping out a tool for that just because ChatGPT can answer "how do I reset my password?" slightly faster. Customer data gravity You cannot put your entire docs website + a knowledge base into a markdown file. I mean, you can. You'd just need a web crawler to index your docs, dump them into a RAG database, and build an MCP server on top. Then maybe index the old tickets so the agent can search history, and... wait, you've just built a helpdesk app. With years of ticket history. Thousands of macros and canned responses. Customer sentiment patterns. Resolution time benchmarks. That one weird workaround for that one enterprise client that nobody remembers but the system does. That's institutional knowledge. That's training data. An AI agent starting from a markdown file has none of it. It's the new hire who didn't read the wiki - except the wiki doesn't exist yet either, because the wiki is the helpdesk history. Compliance & trust Enterprise buyers need GDPR compliance. Data residency. HIPAA. Audit logs that prove exactly who accessed what and when. "I built an AI agent over the weekend and pointed it at our support email" works great for a single-founder startup, but doesn't survive a procurement review. It barely survives a security questionnaire. Actually, it doesn't survive a security questionnaire - it is the security questionnaire's nightmare scenario. So what's the actual play I'm not here to dismiss AI - helpdesk apps need to absorb it. Embed AI deeply into the helpdesk itself: auto-drafted responses, smart routing, ticket summarization, triage, sentiment detection. Give customers the AI benefit inside the tool they already use, so they never feel the need to replace it. Better yet - become an MCP tool in your AI-powered org or even the orchestration layer. Let customers plug in their own AI agents, but manage them through the helpdesk. Routing rules, fallback-to-human thresholds, confidence scoring, handoff protocols. The helpdesk becomes the control plane, not the answer engine. Which, by the way, is exactly what we're building at Jitbit. The future isn't pure-AI support (customers will revolt) and it isn't pure-human support (too expensive). It's the helpdesk that best orchestrates humans and AI together. The markdown file crowd will figure that out eventually - right around the time their first enterprise prospect asks for an audit trail.
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Download Now View on pouet.net Intro In the late 80s, I spent an embarrassing number of hours hunched over my ZX Spectrum, typing in Sinclair BASIC programs and rudimentary assembler routines copied from magazines, trying to re-create the Amiga crack intros I’d seen round at a friend’s house. Obviously, they never came even slightly close - but now, many decades later, I’ve finally managed it! I’m now the proud author of a hand-rolled retro demoscene intro that runs on a stock 128Kb Spectrum. It features all those late 80s tropes: A smooth scrolltext (with ‘leet custom fonts!), a three-channel AY soundtrack, bouncing VU meters and the essential parallax starfield. It’s currently 10287 bytes of code, or 19552 bytes as a complete tape image - which, given I’ve been working on this since December 13th last year, means my average rate of code-production is a paltry ~ 455 bytes per week! This blog post is a technical overview of how I got there, some cool tricks I picked up, and everything I had to learn (and re-learn) about the Speccy and Z80 assembly along the way. It simultaneously rates as one of my favourite side-projects ever, and also the one that most often nearly triggered a foot put through my monitor in frustration. I’ll reflect on all that at the end, but for now if you just want to see the finished product, the download button is at the top of the article and the included .tap cassette tape image should load into any emulator. There’s also a YouTube capture, links to the production on pouet.net, and you can run it from within a web browser by visiting my TNFS site portal - check option 4 for recent uploads. Be Kind, Rewind But let’s skip back briefly to the late 80s. Coming from the world of an 8-bit, cassette tape loading computer, seeing an Amiga for the first time was like encountering something from outer space. Like everyone who saw one back in the day, I was blown away by the amazing graphics and sound on display, not to mention the library of ground-breaking games. But I found myself even more captivated by the mysterious (and totally badass) “intros” displayed at the beginning of pirated games. Created by the software piracy groups that had cracked the copy protection and distributed the floppy-disk based games, they were mini works of art in their own right - music, graphics and usually some cool-looking effect to show off the group’s prowess. There’s a great collection of these intros (or “cracktros”) archived on YouTube. Watch a few of those videos and you’ll quickly notice the “design” tropes that almost every cracktro shares: a cool, edgy logo at the top of the screen (bonus points if it’s dripping blood or in any way “metal”), some boastful text displayed on top of an effect of some sort - usually a scrolling parallax starfield, or rotating 3d object - and a further scroll-text full of shout outs, greetings to fellow pseudonymous crackers and adverts for illegal BBS systems galore. Needless to say, to a kid in the 80s/early 90s this was possibly the coolest thing ever. I thought this one was the absolute bomb when I first saw it. Sine-scroller, pirate BBS adverts, cool logo with a sword - and of course, a starfield. There’s something for everyone here. The music from this is burned into my brain. I think pretty much everyone of my classmates knew this intro given the popularity of Lemmings in the early 90s. Skid Row as a group are still active to this day and this is probably the quintessential Amiga cracktro of the period. Endless Piracy. Edgy. Another cool logo, sine-wave scroller, starfield and boasting text. The classics never go out of style. Another great combination of all the essential ingredients. Cool logo, even cooler text font, scrolling starfield and a scroll-text running along the bottom. Vintage stuff. Logo. Text. Scroller. But no starfield - otherwise a solid effort from Anthrox here :) The demoscene grew out of these intros. The cracking eventually faded into the background, and coders, “graphicians” and musicians all contributed to feature-length productions that showcased their abilities, competed with other groups and pushed the machine to its limits. In amazing feats of ingenuity and pure “code as an art form”, the scene lives on today, with groups producing breathtaking productions like this and this - bear in mind, both of those are running on a 7Mhz home computer equipped with a floppy disk, 1Mb of memory and a sound chip from 1985. But much as I admire the sheer skill and dedication that takes, it’s the early “single screen” scrolly-text-and-starfield cracktros I’ve always found captivating. They took on a sort of mystical quality for me, hinting at a scene and a culture I could only ever experience from the outside - which is exactly why I spent all those hours in Sinclair BASIC, trying in vain to re-create them, and dreaming of the day I’d eventually have an Amiga of my own. The Jump Back I eventually did trade up to a range of Amiga systems, joined a few “scene” groups myself and threw myself into a variety of activities until exams and the end of my teenage years beckoned. I dabbled with Z80 code back then, and at one point knew enough 68k assembly to bluff my way through - partly from the Amiga’s heyday, partly from a few “embedded systems” modules at University where I had to program a set of traffic lights or lift-controllers. Given there’s not much call for that sort of thing at my $DAYJOB, though, it had all pretty much faded from my memory. I have kept working on a bunch of projects in my spare time, and one of my favourites is my TNFS site - sort of an old-school BBS system or interactive “website” for the Spectrum, which grew out of a fun experiment to see how far I could push Sinclair BASIC. It relies on a modern network card fitted to the Spectrum, which is how I came to be chatting to “Desertkun”, another TNFS-protocol enthusiast. He’s now producing a great new WiFi network card for the Speccy, and was kind enough to send me a few of the prototypes to test out for him. I was massively inspired by his hardware and low-level coding chops, and during one of our video calls where we’d been comparing our development setups, he asked why I didn’t write any Z80 assembly myself. A throw-away comment, but the challenge was set! Now, I couldn’t face re-writing the whole site in asm, but I figured I could produce a self-contained intro to promote it in the style of the early “BBStros”, and finally be one of the cool kids with a scene production of my own :) I mean, how hard could it be ? (ooooh - foreshadowing!) Dev Environment My development environment through this was pretty straightforward, and is the same stack I use for developing my TNFS site. I just used a Makefile-driven build system which ran my code through the Pasmo assembler, my fork of zmakebas to build BASIC files, and the FUSE emulator for testing. For final testing on the real hardware, I uploaded my .tap files to my local TNFS server where I could run them on my +3. A few additional tools I have to call out because they ended up making a big difference - one is the amazing web-based “asm-editor” I discovered while looking up Z80 instructions. Not only does this site have a great reference of all the Z80 instructions, but it also has an editor where you can run example code and see how the memory and/or various registers change state. Take for example, the djnz instruction - you can build it and step through the example loop construct one instruction at a time. Or try my example of an add instruction in the screenshot to see how the carry flag works when a bit gets shifted out of a register. Although it uses a slightly different syntax to Pasmo (so I couldn’t drop my code directly in it), it massively helped when manually stepping through things. And lastly, probably the most significant debugging tools I used on this project - a notepad and pen, and my two dogs (say “Hi!” to Biscuit & Pebble…) I’ll write some more about this in the wrap-up, but this really was a highly unusual project for me, coming from decades of much higher-level languages and constructs. Most of my z80 code I only ever really understood after drawing out the bytes and bitmasks, keeping a table of register flags and drawing chunks of screen memory out by hand. And I found my evening walks with the two dogs provided ideal rubber duck exercises, although I’m not sure what they both made of my protracted mutterings about the hl register pair. Either way, debugging-by-dog is highly recommended! The Starting Point So, let’s get started. I followed a great “Hello, world!” example from futurice.com to validate my build environment. Beyond that, the first thing I wanted to do was load in my logo and background image I’d use as a “stage” for the remainder of the planned intro. I wasn’t really sure what I was going to do at this point, just that I wanted my logo at the top, and a scrolltext along the bottom row of the screen. As my TNFS site header already looked kinda demoscene-y, I made a quick edit putting in place two blue guide-bars inside which I’d put further content. Memory map courtesy of breakintoprogram.co.uk A Spectrum SCREEN$ file (usually displayed as loading screens) is just a dump of screen memory, starting from byte 16384, and running for 6912 bytes. The weird layout of this is very relevant later, but in order to display it all you need to do is load your file into that memory location. After a few hour’s work of reviewing Speccy internals and following various guides, I had a very simple starting point for my demo that served as the basis for everything else that came after. org $8000 screen EQU $4000 ; address of the first byte of screen memory, 16384 in dec scrlen EQU 6912 ; total length of the screen memory inc. attributes ula EQU $FE ; I/O port for the ULA to control the border black EQU 0 ; Spectrum colour number, the exact same ones BASIC uses start: ld a,black ; Set the border colour to black using the ULA out (ula),a ; Copy my logo header picture to screen memory ld hl,header ; HL = location of my screen file in this code ld de,screen ; DE = start of screen memory ld bc,scrlen ; BC = 6912 bytes to copy ldir ; block copy, see https://jnz.dk/z80/ldir.html ; busy loop - rest of intro goes here :P hold: halt ; sleep until the next interrupt (1/50 second) jr hold ; then jump back and sleep again, for ever header: incbin "assets/header.scr" ; my logo header/background end start Not much to look at now, but this simple starting point introduced me to important concepts like interfacing with the Spectrum’s hardware (ULA chip to start with, and AY sound chip later) via the out instruction, how to pull in binary files using Pasmo’s INCBIN directive, using the Z80’s block copy ldir instruction, the use of register pairs for 16-bit addressing, and simple branching to labels. Hello World The next step was to print something on the screen and explore some of the Speccy’s built-in ROM routines, which are somewhat analagous to syscalls on modern operating systems. There are plenty of disassemblies and guides to the Spectrum ROM available on the internet, one of the best commented and linked one is at https://skoolkid.github.io/rom/. Using this as a reference alongside the various “Hello, world!” tutorials showed me how this sort of thing is built up: at EQU 22 ; "at" control character used to position the cursor row EQU 11 ; coordinates where to print the message col EQU 9 prstring EQU $203C ; where the pr_string routine lives in ROM ld de,msg ; DE = address of the first character ld bc,msglen ; BC = how many characters to print call prstring ; print the lot ; busy loop is the same... msg: db at,row,col ; equivalent of "PRINT AT 11,9" in BASIC db "Hello, world!" msglen EQU $-msg ; 16 bytes in all, pasmo shortcut, $=program counter I ended up mostly not using the ROM routines in my code as they dragged in all sorts of things I didn’t need, but it was massively useful to understand how they worked as they introduced me to yet more commonly-used constructs. For example, the PR_STRING routine defined here shows how you can build a loop over each character. If you’re just starting out, I highly recommend going over the 8 lines in that routine with a notepad and pen, working out the contents of the registers and following the loop constructs. I also made a version of it in asm-editor you can try. If you click that link, you’ll see a version of the code loaded into the web editor. Click “Build”, and then step through the code using the “Step” button - although no text will be actually displayed (I skipped over the call to the Spectrum ROM “restart” vector that does this), you’ll see the various states of the registers and for example the BC register counting down as each byte of the string is processed. Adding Some Style Problem is, the Speccy’s built-in font is not exactly dripping with demoscene credibility. I wanted to use some stylish fonts and this turned out to be super easy - a quick search turned up Jim Blimey’s awesome font collection, which included a ready-to-use set of assembler files and some instructions which soon led me to these additions in my code: ; CHARS is the address the ROM's printing routine reads to find the font. ; Picking our own font is simply a matter of over-writing this chars EQU $5C36 ; from Jim's docs - POKE 23607=5C36 in hex ld hl,myfont-256 ; HL = font address - 256 as per docs ld (chars),hl ; from now on the ROM draws with it! ; rest of code is the same myfont: include "textfont.asm" ; "Cartoon" font from jimblimey.com There we go! Now that’s looking a little more elite. Sorry, I mean 31337. Strap in folks, we’re leaving lamer city… So at this point, a month or so in to my dabblings and I’d started to get a reasonable understanding of common idioms and was starting to feel like this was a project that might actually go somewhere. The problem started when I moved on to trying to implement actual demo effects: It became very apparent, very quickly, just how much I didn’t know about how this all worked. Not to mention the fact that at this level, you’re really closely exposed to the physical hardware intricacies, including the design decisions and trade-offs that the hardware designers had to make when working with the extremely limited specs of the early 1980s. Cursed Screen Layout The first such problem - and the cause of probably 90% of my pain - is the Speccy’s extremely weird screen layout. Rather than standard bitmapped display you might expect on more modern hardware, it is instead split into 3 sections, each with a set of interleaved rows (so if you keep adding 1 to a screen address, eventually instead of reaching the next row, you’ll instead end up 8 rows down, and so on until you hit the bottom of the section and then loop back to the row underneath where you started!) followed by a block of “attribute” bytes which determine the colours of each 8x8 block. The attribute blocks are the reason why each 8x8 character cell can only have two colours (a PAPER and INK attribute) which led to the garish “colour-clash” of spectrum games and distinctive style where artists try to keep inside 8x8 blocks as much as possible. But it was the layout of the bitmap portion that is such a mind twister. Download the video You can see this illustrated whenever a game reads in a loading screen from tape. You can see each section built up with the interleaved rows one at a time, and then finally the colour and other attributes (like flashing ). There’s a lot of detail at the fantastic Break Into Program site. In the defense of the designers, they were working with extremely limited hardware and I don’t think the Speccy was ever imagined as a games machine. When you start shuffling bytes around, you realise that this approach is really optimised for displaying text which is neatly arranged into 8x8 character boundaries. For example, using this “scrambled” bit order, if you have a screen address in the hl register pair, you can quickly get to the next pixel line of a given address by simply incrementing the “high” byte. There’s a bunch of other “cheap moves” you can make by simply shifting bits around: Move Instruction Right 8 pixels inc l Left 8 pixels dec l Down 1 pixel line inc h Up 1 pixel line dec h Down 1 character row add 32 to l It was a reasonable choice for a machine that would probably spend a lot of it’s time displaying BASIC program listings - it’s only when you start trying to write demo or sprite routines that it starts to feel really weird. This also means you’ll pretty quickly need a routine to convert X,Y addresses to the relevant memory addresses. Again, L Break Into Program has a useful routine and if you disassemble more or less any spectrum game or demo, you’ll find a version of this procedure somewhere. And yes, this all became horribly relevant later on… The Scroller Download the video Admittedly, not the most interesting demonstration - but this was the first time I had made something move on the Spectrum’s screen with assembly! I watched this with pride more times than I care to admit :) I had a snazzy logo and “Hello World” text, but that doesn’t make for a very interesting intro! The first effect I wanted was the scrolltext - without that, it’s not really an intro. Now, the Amiga had all kinds of hardware sprites, blitter operations, custom chips but the Spectrum had none of that. I was going to have to work out how to do things the hard way - “banging on the metal”, literally by shifting bits around the screen memory by hand and having the CPU do all the work. This is where understanding the Speccy’s weird screen and character cell layout is so important. It turns out there’s a neat trick as long as I stay inside one character row - there’s a RL instruction, which takes a byte and “rotates” it left. It inserts whatever is in the carry flag into the rightmost bit, and whatever gets shifted out ends up in the carry bit again. That means if you string a bunch of them together, you can move a set of pixels across the screen - the moment they “fall off” one character cell, they end up in the carry flag and then the next rl instruction inserts them at the beginning of the next character cell to the left. Repeat 32 times, and you’ve just moved a pixel (or set of pixels) across a line of the screen: linestart EQU $4880 ; leftmost byte of the line 12 rows down lineend EQU linestart+31 ; rightmost byte column ($489F) linelen EQU 32 ; one whole line is 32 bytes (character cells) across dot EQU %00000001 ; the dot "shape", just one pixel lit at the far right end newdot: ld a,dot ; load the dot shape (only rightmost pixel lit) into a ld (lineend),a ; store it in the rightmost byte of the line, pixel is now lit frame: halt ; wait for the next frame, otherwise it whizzes across too fast to see ld hl,lineend ; hl = last (rightmost) byte of the line ld b,linelen ; loop counter, 32 bytes to work through or a ; trick to clear the carry flag, or against itself leaves a register ; unchanged but clears various bits including the carry flag ; see https://jnz.dk/z80/or_r.html shift: rl (hl) ; rotate this byte left (00000001 -> 00000010) dec hl ; point hl at the next byte to the left djnz shift ; loop construct: b=b-1 and then jump back to shift label until b=0 jr c,newdot ; now we've shifted the whole line, so if the carry flag is set now it means ; the dot has just left the screen, so we jump back to the start jr frame ; otherwise it is still somewhere on the screen, so keep shifting! Download the video Hell yeah. It’s almost a proper scrolltext now! Wrapping this in another loop that increments h each time (remember - that gets us moving down a scanline) gets us moving an entire character cell. Here you can see it moving an entire row of my “Hello world” message. There was however a lot more work needed to make a proper scrolltext, with each letter appearing smoothly. I started off by just printing an entire character at a time on the right-hand edge of the screen - it worked, but was pretty ugly as you saw each new character appear at once in the right-hand side of the screen, scrolling 8 pixels over and then the next character flashed up. Instead, I wanted to make each character appear pixel by pixel and that required a bit more bit juggling. The routine I ended up with effectively streams each character in, line by line, pixel by pixel using the font data directly instead of calling the ROM print character routine. It does this by looking up the ASCII code for a character, and then fetching the corresponding font representation into a 8-byte buffer, one byte for each line of data. The font data starts with the space character (character code 32), so a lookup is simply font code base address + (ascii code - 32) * 8 to get to the bits for that letter. Arranged into an 8x8 grid, the bits for the letter H in the font data look like this. For each row of bits, I shift the line left using a neat trick. The byte is loaded into the a register, and then by adding itself to itself - add a,a we shift the value left (in binary, multiplying by 2 moves everything over one bit) so that the pixel I want to draw ends up dropping into the carry flag. This is an idiomatic way of doing it in Z80 code as it’s faster and smaller than the sla instruction. And every cycle quickly adds up when you’re re-drawing 256 bytes every frame! The character buffer then looks like this, with the top line shifted. Now, with the hl register pair pointing at the correct location on the screen, I can then use the rl trick discussed above. This shifts a scanline from the bottom character row of the screen left by one pixel and draws my pixel in the rightmost position by moving it in from the carry flag. Looping 32 times over this moves the entire row by 1 pixel with my new pixel inserted at the right. I then repeat this step again using inc h to move down one scan line until the entire character column has been drawn. At this point, the character buffer looks like this, and all 8 lines of the bottom screen row have all been shifted left by one bit by looping over all 32 character columns. The whole thing then repeats another 7 times until the entire character has been smoothly scrolled onto the screen. So just to re-state this because I think it’s worth the emphasis - just to scroll a message across the bottom of the screen, we’re having to loop over and re-draw 256 pixels every frame! It shows how much faster assembly is than the BASIC interpreter built into the spectrum’s ROM. I found it amazing to see my code finally working and imagining all the bits flying around and registers flapping away. It really makes me appreciate just how much effort went into creating the games I played back then. Music The original Amiga module I converted. A proper 1980s ear-worm! Of course, any good intro needs some music. On the Amiga, the standard was the “tracker” module format, which has a long and involved history of different forks, versions and tweaks. A song is built up from a series of patterns, each made up of rows of instructions. Each instruction usually includes note or pitch information, which sample to play and various parameters such as volume, effects - or in the case of some instructions, which position in the song to jump to. In many ways, it’s almost like a programming language for music. Using ProTracker as an example, a typical note cell is 4 bytes, shown on-screen as something like C-2 01 C20. That breaks down into three fields: the note and octave (C-2), the sample number (01), and the effect and its parameter (C20 - in this case, “set the volume to $20”, which is half of the maximum $40). A close-up of Protracker playing a tune. Note the VUmeters - another classic demo effect I would pinch later on! For an impressive demonstration of what’s possible with a tracker and to see what the note data looks like on-screen, check out the work of h0ffman, and in particular his winning “Professional Tracker” entry from the Revision 2014 competition. He’s an undisputed master of the science (or art!) of tracking, and his “Secrets of Protracker” talk gives a great overview of what’s possible. The Amiga’s sound hardware far eclipsed anything else on the market at the time, and the ZX Spectrum is paltry by comparison. The original 48K models only offered a rudimentary “beeper”, but the later 128K models included a 3-channel AY-3-8912 sound chip. This was very popular in 8-bit micros of the time, and a more-or-less identical variant was also used in the Atari ST. While it only offers basic waveforms and sound processing, it does enable multi-channel “chip music”, and so it became the mainstay of the ZX Spectrum demoscene. It also spawned a variety of SoundTracker clones on the Spectrum itself, although most musicians these days prefer to work in modern tools like Vortex Tracker II, which runs natively under Windows. The Conversion Pex looking back on his demos - this starts at the point where he features my letter and plays a bit of my cover version! For my intro, I wanted to port an Amiga module - and I had the perfect one in mind. One of my favourite Amiga music disks was “Sounds Of Gnome”, released in 1989 by the Swedish duo “Mahoney & Kaktus”. Mahoney also wrote NoiseTracker, one of the first really widely used trackers on the Amiga, and the program that served as my teenage introduction to making computer music of my own. Back in 2018 I made a rock cover of one of the other tunes on that disk, and wrote to Mahoney (real name “Pex”) about it. He ended up showing my “music video” at a demo conference, which I am eternally grateful for! So it seemed only fitting that I mangle another song from that collection with a Spectrum conversion… Sorry, guys! I picked the track “Milkman” which was written by “Glue Master”, an associate of Mahoney’s who had a few of his tracks featured on the compilation. It’s an ideal track for converting: It’s short (only 7 patterns in total), most of those patterns share the same chord sequence, and it looked fairly easy to squeeze the original 4 channels down into the Spectrum’s 3. Plus, it’s an incredibly catchy tune and I knew it well - I’ve been listening to it for 35+ years and often jam along to it on guitar or bass. The conversion started off pretty easily: all I really had to do was copy the patterns note-for-note from the Amiga mod, which I had open in OpenMPT as my Windows tracker. Below is a session with both trackers open on the same pattern - the original Amiga mod on the left, and my 3-channel Spectrum conversion on the right. Note the 11.7 in the 3rd channel of the Spectrum version. This is a “pitch slide down” effect in Vortex Tracker syntax, which drops the pitch by about a quarter-tone. It’s repeated on the next line, so the overall effect is a slide down from the A# that leads in to the next bass note. The original Amiga mod does the same thing using its own syntax - those are the 202s you can see on the same notes, at the bottom of the 4th track. Using just a single “beep” sound for everything was enough to check everything was working, and after a few weeks of hacking on it and re-arranging things in the evenings, I had a basic version which sounded surprisingly good for a first draft: Download the MP3 instead. I have to give a special mention to this forum post which was a massive help getting me started. It’s probably the best introduction to Vortex Tracker I’ve found - many, many thanks to the original author for taking the time to write it all up! The real challenge was making it sound as close to the original as possible. That meant building up a library of better-sounding samples for the different parts, and making extensive use of Vortex Tracker’s “ornaments”. Vortex Tracker comes with a great selection of sounds, and fortunately I’m also a weirdo who likes to listen to chiptunes in the background while I work! So whenever I found something particularly enticing, I filed it away for later pilfering inspiration. A Vortex Tracker sample isn’t really a “sample” in the Amiga sense of a recorded sound - it’s a definition of how a note sounds, one line per frame. Each line can mix in a tone or the white noise generator (useful for snare effects and suchlike), along with various other parameters. Ornaments, on the other hand, give you extra control over what pitch a note plays - and this enables really useful tricks like “arpeggio chords”. For example, an ornament of 0,4 makes the channel switch rapidly (25 times a second) between the note being played and the one 4 semitones above it. It happens so quickly that it sounds much like two notes played at the same time, which means you can build up full-sounding triad chords using only two channels. Take the opening chord in my fully converted version, Cm: It plays C in the first channel and the minor 3rd (D#) in the second, then I apply an ornament to the second channel to bring it up 4 semitones to the 5th (G). That gives all three notes of the chord, while keeping the 3rd channel free for other parts. As well as making much more efficient use of the limited 3 channels, this also gives Spectrum music that characteristic “warbling” sound, which I find really appealing in a retro kind of way! Between tricks like this and samples that mix tones with white noise (to make a combined “bass-snare” sound, for example), I managed to condense the full track down to 3 channels. Many months later, I have to say I’m really pleased with the final result. Playback The original site that was home to Vortex Tracker, documentation and other resources appears to be offline at the moment. I managed to grab a copy of everything I needed from archive.org - you’ll want the PTxTools.7z file for the playback routines discussed here. The playback was simple in theory: As this overview notes, you basically just pull in the player routine, include your module file and call the playback routine once per frame in your main loop. The catch is, none of the source code versions supplied in the archive worked with my Pasmo assembler. Fortunately, there is a pre-compiled binary object shipped alongside the source (VTII10bG in the PTxTools/PT3Play directory). This just has to be loaded in at address $C000 - this cannot be changed, as it has lots of absolute addresses baked in. My code to handle module playback now looks something like this, with the binary module loaded in place: ; Define the start address of the player routine and functions we need player EQU $C000 ; hard-coded org address of binary player plinit EQU player+3 ; init function in docs, module address in hl plplay EQU player+5 ; play and move on one frame ; from the docs - this "analyzes PT3 module header and prepares ; corresponding note and volume tables" ld hl,moduleimg call plinit ; main loop hold: halt call plplay call scroll ; other effects / routines go here... jr hold moduleimg: incbin "assets/music.pt3" Starfield Download the video Well, that didn’t work as hoped. TNFStro - tortoise edition. This brings me to the main event. No self-respecting cracktro is complete without a starfield! My first, naive approach to the classic starfield effect was to scatter random stars across the screen, then move down each scan-line applying the same rl trick I’d used for the scroll-text. I figured I could get parallax by shifting each row a different amount: One pixel for the first row, two for the second, three for the third, then back to one again, all the way down the screen to give the impression of several “fields” of stars moving at different speeds. It turned out there were two major problems with that approach. Firstly, shifting an entire row smeared whatever else was on it along with the stars - which I’d expected, and had filed away as a problem for future me. The bigger issue was speed: by the time I’d finished the first three rows I’d already performed hundreds of shift operations, and it was nowhere near fast enough to fit inside a single frame. Everything crawled across the screen, and the music playback slowed down so much that you could actually hear the arpeggio ornaments warbling away as separate notes. Clearly I was going to have to keep track of the individual stars instead. I found this routine, which was more-or-less what I had in mind and started me off with the idea of a structure to hold the state of each star. It also uses a screen address lookup much like the one from “Break Into Program”. Download the video Dammit. Back with another funeral dirge rendition :( That got things moving, but the co-ordinate lookup and tracking proved expensive to do (it has to run for every star, every frame as well as keep track of the old position for erasing) and I’d been ignoring the bigger question how to display stuff on top of the starfield. My original idea was simply to draw the stars and then paint text over them each frame, which blew the frame budget just as comprehensively as my first attempt. If I wanted something more interesting than an empty starfield, I’d have to keep track of which cells were occupied by text and avoid drawing stars in them in the first place, rather than over-painting them every time. After lots of scribbling in my notepad and visualising rows of bits, I eventually solved both challenges by “cheating” fairly liberally. So now, I don’t generate a random starfield at all. Instead, I built a table of pre-calculated Y and X position pairs: stdata: defb 109, 25, 88,182, 42, 96, 155,226 defb 59,254, 137,169, 160, 84, 125,193 ; ... and so on, for 32 stars ... This saves faffing about with an RNG, and once I have a layout that looks good I know it’ll always look good. I can also “fudge” things and ensure no two stars share the same y co-ordinate which sidesteps a whole class of problems like stars sharing a scanline, and having to deal with them overtaking each other. The “random” layout is generated by a simple Ruby script: #!/usr/bin/env ruby PAIRS = 32 PER_LINE = 4 # pairs per line Y_RANGE = 40..175 # exclude rows taken up by my logo & bars X_RANGE = 0..255 raise "y range too small" if Y_RANGE.size < PAIRS # no duplicate y values ys = Y_RANGE.to_a.sample(PAIRS) pairs = ys.map { |y| [y, rand(X_RANGE)] } pairs.each_slice(PER_LINE) do |row| body = row.map { |y, x| format('%3d,%3d,', y, x) }.join(' ') puts "defb #{body.chomp(',')}" end When the routine initialises, I convert those co-ordinate pairs into a table that tracks the state of each star. So rather than storing a position and translating it to a screen address every frame, each of my star records now looks like this (offsets from the base address): STSCR EQU 0 ; screen address of the byte the star is in, e.g. $4123 STOCC EQU 2 ; a pointer to the "occupancy check" table cell STMASK EQU 4 ; the star's bit pattern, e.g. %00010000 STSTEP EQU 5 ; "speed" - num. of pixels this star travels per frame The key thing is that there are no X/Y co-ordinates at all. For each star I store the screen byte it sits in and the bit mask within that byte, so it’s already in the form the screen writes need. That means no address conversion per frame, just simple bit shifting and rotation. Moving a star is then dead simple. I rotate its mask left with rlca, and when the bit rotates out of bit 7, it lands back in bit 0 with the carry flag set. That’s the signal I need to move the star one character cell to the left, which is one of the “cheap moves” from earlier. Because I’m tracking which cell each star is in, the collision check comes almost for free. That’s what the second pointer is for: STOCC (Star Occupancy) moves in step with STSCR through a table holding one byte per character cell. The “typewriter” routine sets a byte to 1 for every cell containing a text character or the cursor, so checking whether a star is hidden behind text is a single or instruction. If the cell is occupied, I skip drawing the star but carry on rotating and stepping it along until it reaches a cell where it can be displayed: ld l,(ix+STOCC) ld h,(ix+STOCC+1) ld a,(hl) ; A = the occupancy check for this cell or a ; test A against zero jr nz,stmove ; it's occupied, so leave the screen alone Parallax is still handled by moving each star a different number of pixels per frame, but the cost is a lot lower this time as I’m only touching the cells the stars actually occupy, rather than every byte of every row. Download the video That’s looking more like it! The typewriter routine is a simple copy of the font data from memory, and is very cheap as we can use the “cheap moves” to quickly fetch the 8x8 block. I also skip drawing any space character so it leaves the “occupancy cell” unmarked. This means the stars keep drifting through the gaps in the text - you can see here the odd star passing in between the words. I switched to ALL CAPS writing for the final version which helps the effect even more as the font is quite blocky, so you don’t really notice stars skipping the spaces inside a glyph at all. Misc Notes A few odds and ends that didn’t warrant a section of their own… VU Meters Some sort of graphic display bouncing along with the audio playback was another common early demo trope. I did originally consider a real-time graphic equaliser, but that would have been far too complex, probably in terms of spare cycles per frame, and definitely in terms of my limited mental capacity at this point! So I settled for a simple set of bouncing meter bars instead. It’s worth a mention mostly because it gives me an excuse to link to the awesome chibiakumas website! I just love the late 90s web design on display - one can argue that readability and accessibility take a hit, but it’s just so much fun to encounter a site that still looks like this. It’s a clear labour of love and there’s a wealth of content there as well, if your eyeballs are up to it. Their guide on Making Sound with the AY-3-8910 was what showed me how to get the data I needed to draw the meter bars. The examples write a register number to $FFFD to select a register, and I realised that once a register is selected, I could use the in instruction to read its value back out instead of writing a new one. As the page says, R8, R9 and R10 hold the channel amplitudes, so they feed nicely into the height parameter for drawing a bar. Getting the amplitude for channel A is then as simple as: ld a,8 ; Channel A register call ayread ; ... rest of code here ... ayread: ld bc,$FFFD ; Register select port out (c),a in a,(c) ret Twinkle, Twinkle, Little Star This is a simple effect that makes the header logo a little more interesting. I’m not sure where I originally got the idea - I’ve definitely seen something like it on a few late 80s/early 90s demos, though. All I wanted was to pick random star dots in the logo background and animate them. Here’s the header image loaded in ZXPaintbrush with the character cell grid showing. By happy chance, there are four stars which each sit neatly inside a single character cell with enough surrounding space, so they can be used to give an animated “twinkle” effect by drawing a cross out from the centre point and back in again. These dots map to the following co-ordinates, which target the top scanline of each fully-grown star (two pixels up from the centre): twkdata: defb 1,5 ; char row 0, col 5, centre y=3 ink 5 defb 1,20 ; char row 0, col 20, centre y=3 ink 1 bright defb 26,7 ; char row 3, col 7, centre y=4 ink 4 defb 25,22 ; char row 3, col 22, centre y=3 ink 6 bright The “twinkle” routine itself is simple enough: it adds a pixel on either axis to grow the star, waits a few frames, then shrinks it back down again. The interesting bit was how I made the twinkle order pseudo-random. Remember that my starfield was entirely pre-calculated from a data table generated by a Ruby script, which meant I’d never actually needed a random number generator in assembly. From Jonathan Cauldwell’s “How To Write Spectrum Games” e-book, I found another great “hack” which simply walks through the start of the Spectrum’s ROM, picking out random-looking bytes as it goes. As he says, he uses it in most of his games, and it does the job in a really simple way - as long as you stay below the block of structured, repeating data that sits 8Kb into the ROM. twkrand: push hl ld hl,(twkseed) ld a,h and 31 ; keep it within the first 8k of ROM ld h,a ld a,(hl) ; the "random" byte inc hl ld (twkseed),hl pop hl ret Out Of Space About halfway through writing the intro, I hit a fairly predictable problem: I had run out of memory. In an attempt to keep everything self-contained in one block of code, I was pulling all of the assets (the screen background, the player binary, the music file etc.) into the program itself, and then using the ldir block copy instruction to move each one into its correct location. Since that meant effectively storing every block twice, and the player routine had a hard-coded start address of $C000, I quickly ran out of room and my code started crashing into the playback routine. The simplest option was to split things out into separate code blocks, load each one directly to the address it needed to live at, and wrap the lot in a multi-stage BASIC tape loader: 10 CLEAR 32767 20 BORDER 0: PAPER 0: INK 0: CLS 30 LOAD "" CODE 40 LOAD "" CODE 50 LOAD "" CODE 60 RANDOMIZE USR 32768 This loads the main program, then the player routine directly into $C000, and finally the background screen straight into screen memory. It does mean the background starts appearing before the demo has fully loaded, but as I imagine most people will be seeing this running in an emulator or on my TNFS site, it doesn’t really matter. Plus, at this point I was in danger of disappearing down yet more rabbit holes (I still really want to work out how to do multi-colour border effects!) and I’d never have got this thing released. The Zen Of Z80 This whole project is a really weird one to look back at. On the one hand, I’ve fulfilled a childhood ambition and have something I’m very proud of. It’s also pretty unusual these days to end up with a binary where you can say pretty much what every single byte is doing and the story of how it got there. But on the other hand - I now have an answer for why I don’t code in assembly: It’s because I value (what’s left) of my sanity! The thing is, in order to write code like this you have to start thinking like the machine itself. You have to visualise the registers and the status flags flapping away, graphics as lines of bits slotted into strange orders, loops and conditionals as binary logic and so on. Getting this close to the hardware definitely brought about a greater sense of attachment to the hardware of my childhood, and it’s easy to see why assembly coders and sceners get so passionate about it. That said, I’m in no hurry to start re-writing my body of work in assembly! The projects I really enjoy are those that give me an excuse to learn something for the sheer hell of it, and to slow down a little from the ever-increasing velocity and demands of the modern work world. Going back to Z80 code is probably about the furthest I could have taken this, short of going into hardware hacking. I found it at times an intriguing puzzle, often a frustrating exercise that nearly had me throwing in the towel at several stages. This project has certainly taken the longest to go from the “idea” stage of any given feature to any kind of meaningful output. True, I didn’t spend every day of the last year working on it - my actual coding time was probably only a few hours over a couple of evenings a week. But I’ve certainly been thinking about it and pondering it most days (as my dogs will attest). The biggest breakthroughs and “aha!” moments usually didn’t come from behind the keyboard; they came from scribbles in my notebook and thinking about processor states while doing something unrelated. It has however given me massive appreciation and respect for the coders who pull this stuff off and make it look easy. And that goes double for those kids and bedroom coding superstars who managed all of this back in the 80s, and had to work it all out by experiment themselves. I only managed to get this far because of numerous books, online tutorials, GitHub repositories with sample code, YouTube videos… I can’t imagine how much longer this would have all taken me if the only resources I had were my Spectrum, a cassette tape recorder and a notepad. So, as I draw a line under this project - for now! - I raise a glass, and in the words of h0ffman: “Shout out to the hackers, graphicians and protrackers.”
A decade ago, a little bit of history was made. I didn't realize it, but a colleague made a great point, one of those real mind-changing points that seem too obvious to admit same-day. But, the next day, calver.org was born. At the time my team maintained the Python infrastructure for eBay and PayPal, and we were stuck deciding whether we were really ready for a "major" 1.0 release. Semantic Versioning was the only game in town and "major" means "big", right?! Thankfully, a wiser colleague mentioned: Ubuntu and Twisted don't struggle with version number debates. They slap a date on it and keep shipping. In fact, their date-based versions were even better because you always knew where it stood, in terms of updatedness and support. The only problem is that no one really knew about it. Somehow, this problem solving versioning alternative, arguably as old as history itself, had gone nameless for millenia, conspiring to make me feel foolish in an office meeting. Never again! Ten years of adoption Fast forward 10 years, we've seen CalVer adopted by Apple, Nvidia, JetBrains, and countless others. (We have a timeline!) The site may have more inbound links than any other project of mine. Apple made the biggest jump, at WWDC 2025: iOS went from 18 to 26 macOS from 15 to 26 watchOS from 11 to 26 and visionOS from 2 to 26 All landing on one, consistent number like a car's model year. I still remember the texts from the Venn diagram fanbase of my friends who love Apple and reasonable versioning. No such texts from when NVIDIA announced calendar versions across the GPU Operator, RAPIDS, and its monthly NGC containers, but still very cool. Open source, too: Home Assistant, pip, CockroachDB, and yt-dlp all ship on dates, with plenty more on the users page. The conversation even reached the language core; PEP 2026 proposed versioning CPython as 3.YY, and it almost happened, too. And it's never too late, time marches on! Fixing the notation But I don't think I got every detail right from day 1. That's the main motivator for CalVer 26. It's high time to start righting a couple idiosyncratic token design choices, starting with some additions: Meaning Before 26.0 26.0 Full year YYYY YYYY Short year (6, 16) YY YY Zero-padded year (06, 16) 0Y 0Y Short month (1 ... 12) MM M Zero-padded month (01 ... 12) 0M 0M Short week (1 ... 52) WW W Zero-padded week (01 ... 52) 0W 0W Short day (1 ... 31) DD D Zero-padded day (01 ... 31) 0D 0D Seeing double First, the doubled letters. From the first version (16.6), MM and DD meant the unpadded month and day, which reads backwards to anyone who knows date formats (ISO 8601's YYYY-MM-DD, Java, moment.js, day.js), as some community members correctly pointed out. I was ready to flip them, until I checked what people actually use: most projects with a YY.MM.MICRO badge (conda, Twisted, Ansible's tooling) don't pad, and more than a dozen other version management tools (like bumpver and bump-my-version) implement the old meaning. So, it's too late to flip MM's meaning. Instead, 26.0 deprecates it and offers a more explicit and hopefully clearer option: M is the short month, 0M the padded one, and MM is a technically-retired synonym for M. In case you're wondering, the explicit 0M was me being overinspired by Ubuntu's approach, perhaps: 6.06 pads its month but not its year, and YY.0M says exactly that. To pad or not to pad I think it's worth a detour into why padding is even a thing anyways. It's become important now that new ecosystems have emerged that enforced SemVer formatting semantics, and I wanted clear guidance about on the spec site. SemVer forbids leading zeros outright, so Cargo rejects 26.04.0 and Go modules reject v26.04.0. Even Python's packaging spec normalizes leading zeros away, so you can tag 2026.08.19 if you want, but PyPI will still show 2026.8.19. NVIDIA's GPU Operator docs put it this way: "Zero padding is omitted for month to be still compatible with semantic versioning." CalVer was always intended to drop in where SemVer was used. So 26.0 recommends unpadded (YYYY.M.D) as a sane "pure" default for software libraries. But libraries are not the only objects of versioning schemes. The exception is a version that becomes a filename, an image tag, or an object-store key that gets listed lexically. There, padding keeps 26.10 sorted after 26.09, which is why Ubuntu, NixOS, and NVIDIA's own NGC containers pad. More evidence of teams designing their versions. We love to see it. Our FAQ has a longer discussion of the padding issue, as well. Optional segments There was never any rule against them, but 26.0 makes optional trailing segments more explicit with square brackets. Now, yt-dlp's scheme can finally be written down: YYYY.0M.0D[.MICRO]. For the CalVer badges I could find on GitHub, they all stay valid for now. I've got a note on the deprecated spellings and a new copy-paste badge section for new ones. What else is new? It's always a great time to add more citations to the site. A spec changelog; the spec now versions itself: 16.6, 19.7, 26.0. A FAQ: breaking changes, same-day releases, and padding. The users page, rebuilt by category, with past users of note (schemes change; that's fine) and tooling. Case studies: Apple and NVIDIA in, yt-dlp replacing youtube-dl. Much of the thinking behind these changes happened in the GitHub issue tracker over the years, and 19 or so issues close with this release. That's where ideas for CalVer should go, so by all means, open an issue, and we'll get it sorted! In due time, of course. In closing, I can't believe I still love belaboring these numbers so much. Thanks to all (but especially Mark, Glyph, Hugo, issue reporters, translators, and maintainers) for the discussion, and ultimately making the most timely versioning system a timeless classic. See also 2016 announcement Designing a version My Yap on Why CalVer beats Semver
Four sincere attempts at OKRs, four failures, and every time: "you didn't do it right." Maybe the framework doesn't fit you -- so how do you find one that does?
Multiple concurrent writers. Multiple processes. Same SQLite. No modifications.
Brilliant jerks, ZIRP-era managers, and how psychological safety lost the plot. Part 3 of my conversation with Dr. Cat Hicks.