My view is that software engineering is splitting into two paths. One is deep craftsmanship. The other is guided operators who know how to steer tools, systems, and LLMs toward the right result.
I am keen to hear where others agree or disagree, and how you see this playing out in real teams.
Most coding CLIs I've seen lock you into one provider or requires you to bypass by changing BASE_URL and has a lot of conflict. That works fine if you're committed to one vendor for coding cli harness, but it breaks down when you want to run local models, test different providers, or avoid API costs entirely.
So we tried a different approach. Instead of hardcoding a provider, Autohand code lets you swap between OpenRouter, Anthropic, OpenAI, Ollama, llama.cpp, and MLX from the same codebase. Switch models mid-conversation if you want.
High level, the design optimizes for three things:
Machine orchestration: stateless execution, structured outputs, designed for CI/CD and batch runs, not just interactive use
Auto mode: autohand -p "fix the tests" --yes --auto-commit runs the full task without prompts. Three permission levels plus granular command whitelist/blacklist
Skills system: modular instruction packages that activate on demand. Run --auto-skill and it generates skills tailored to your project
One thing that's been surprisingly useful: because it's provider-agnostic, you can prototype with a fast cheap model, then swap to something heavier for the actual run. No code changes, just config.
It's TypeScript + Bun, 40+ tools (file ops, full git, semantic search, multi-file edits), sessions persist and resume.
Today we are sharing a deep technical guide on how we built Git Flow Automation in our Evolve platform. It solves a real engineering problem: how to run hundreds of agent tasks in parallel across a codebase without conflicts, without slowing down, and without breaking CI.
Rather than simple scripts or CI tricks, we use Git worktrees to give each agent its own isolated branch and working directory. This lets each agent run tests, detect conflicts, and even roll back individual tasks. We also built conflict detection, AI assisted resolution, and merge strategies that keep history clean and safe for teams.
Here is my take based on 20+ years of experience in Devtools and dealing with lots of large code bases.
The guide walks through:
Why sequential execution fails at scale
How parallel worktree orchestration works
Task lifecycle and dependency ordering
Conflict detection and automatic resolution
Testing per task and rollback controls
Merge strategies and commit hygiene
Safety limits and observability tooling
This is a technical system design share, not a product announcement. I would love feedback from builders and maintainers who work on large codebases or autonomous tooling.
A few weeks ago I shared some thoughts on intent weaving in AI coding agents. Today I would like to invite the community to our private beta of Evolve.
Evolve is an AI software engineer designed for long horizon workloads. It uses reinforcement learning style feedback loops to learn from past mistakes, improve future decisions, and reduce repeated human intervention when working on real codebases.
We are early and actively looking for feedback from people who deal with complex systems, legacy code, or long running engineering tasks.
Very interesting research on this, keen to colab with you folks, I've been building a few experiments for old GTX GPUs to extend lifetime of them with matching performance of tokens for Smol, igor [] autohand.ai let's chat.
As we build the capability, our intention is to give the tools for companies to compete with FAANGs, even if they don’t have the engineering excellence to do.
Today we are warning the entire community, stop using companies providing APIs for coding tasks on your company source code.
I’d love to have different opinions here and create a better version of the future together.
I wrote this before I left GitHub and how I’d like to see Microsoft invest in this area, but it was too futuristic, considering how the market has evolved today, I decided to make this public.
If you want to know more about what I’m doing next www.autohand.ai
Wow, OCR is now basically a general domain. I remember when I spent like a year trying to create one for receipts. Took me 6 months of data curation to prepare.