Reflections
ChatBotKit Reflections Topics for coding
ChatBotKit is a conversational AI platform that helps you build, train, and deploy AI-powered chatbots and virtual assistants for your business.
- Autonomous Coding Is HereOpen weight models are now good enough to write real code, which removes the cost that kept autonomous coding out of reach. That is why we run fully automated coding systems in the open, where anyone can watch them work.
- How People Burn So Many TokensI keep reading about teams spending fortunes on coding agents, and I genuinely don't recognise it. We run agents by hand and overnight in CI, and the bills stay small. Here are a few reasons why.
- I Am an AI VampireAn AI vampire is someone too productive to stop, working through the night because the model keeps answering. I have lived it twice and I am certain that most teams will not survive that pace.
- AI Revived an Old Failed IdeaA precise, unambiguous spec is just code wearing markdown. English-like programming languages have been tried many times and they did not stick for a reason.
- The Good Models Got PulledThe best coding models are no longer available on standard subscriptions. Providers are pulling their strongest models while customers pay more and get less.
- Compress, Don't ExpandTreat the LLM as a compression tool. Spend most of your time exploring and discarding ideas. Build only the one that survives.
- On Feedback LoopsExplores why autonomous coding agents require automated feedback loops - linters, type checkers, and unit tests - to operate independently over long periods, and why replacing human feedback with fully automated signals is a prerequisite for truly agentic systems.
- The Discipline of Not BuildingCoding agents made feature delivery almost free. But features were never the goal. Every feature you ship is a liability you maintain forever. The real discipline is knowing which ones to leave on paper.
- AI Psychosis and the Dunning-Kruger LoopAI tools make you feel like the expert in the room. But feeling competent and being competent are different things.
- The Rise of Micro Coding AssistantsPremium AI models are subsidized and unsustainable. Open source models are not perfect but they do not need to be. The future of autonomous coding is not one giant agent. It is many small ones, each doing one thing well.
- The Superstition of Vibe CodingB.F. Skinner's pigeon experiment explained human superstition decades ago. The same operant conditioning now drives vibe coding - variable reinforcement, ritual prompts, and dopamine hits from tools we do not actually understand.
- Not Reading Code Is Not a FlexSome developers brag about never reading AI-generated code. That is not progress. It is a role that can no longer justify itself. The human plus LLM combination is the real differentiator, not blind delegation.
- Everyone Is Building Claude CodeThe AI industry is drowning in homegrown coding assistants that are months behind the commercial alternatives. The hard problem was never the tool. It is figuring out what the tool should be building.
- AI Could Be the End of Open Source as We Know ItSeveral converging forces - from AI-assisted coding flooding maintainers with low-quality contributions, to license-evading clones, to the commoditization of code itself - are creating a toxic environment that threatens the foundations of open source software.
- When Fast Looks SmartAI produces code faster than humans. That doesn't mean it produces better code. Confusing speed with intelligence is a trap - and daisy-chaining mediocre systems doesn't make them brilliant.
- The Iceberg Under Every CodebaseWe only ever see the surface of the software we use. That illusion of simplicity is why people think AI can solve any software problem - and why developer jobs aren't going anywhere.
- Verification Is Easier Than DiscoveryExplores how the P vs NP insight maps onto AI-assisted development and test-driven design, arguing that discovery comes before verification and that AI shifts the bottleneck from writing code to evaluating it.
- Most Code Deserves to DieWhen AI agents make code generation nearly free, the bottleneck shifts from writing to evaluation. The teams that learn to discard code ruthlessly and select with taste will build the best software.
- What Nobody Tells You About Software Maintenance in the AI EraWhile AI can write code faster than ever, software maintenance remains the most challenging and overlooked aspect of software development. Explore why this hidden complexity matters more than ever.
- Where AI Coding Agents Go to DieExplore the complexities of building an auto-scrolling component for chat interfaces and discover why AI coding agents struggle with seemingly simple tasks that require coordinating multiple event systems and managing complex state. Learn from real-world testing and insights.
- Why AI Coding Agents Create More Work, Not LessExplore how AI coding agents are reshaping the software development landscape by creating more work for developers, increasing demand for coding, and leading to burnout, rather than replacing jobs. Discover the implications of this productivity paradox.
- Before AI Slop We Had Spaghetti CodeThis article highlights common programming terms that describe coding issues, emphasizing that developers' concerns are rooted in long-standing practices rather than mere resistance to AI.