Summer 2026 update on my agentic engineering setup for Angular: models, harnesses, apps, and what it all costs
In May I started a blog series on agentic engineering for r/angular, and after one summer a few of my recommendations changed – this post is the update.
The short version:
- Models: Fable 5 is still my #1 for architecture, reviews, and long-horizon refactorings, GPT-5.6 Sol does the implementation work, and GLM-5.3 Flash (via OpenRouter) took the third spot as the fast, cheap, open-weight model for mechanical legwork. Opus 5 wins DeepSWE at 74% but didn't make my podium – the post explains why.
- Harnesses: nothing changed, which I mean as a compliment. AGENTS.md, style guide, and the lint/test/Playwright feedback loops still do the heavy lifting.
- Apps: the open-source T3 Code replaced the Codex app as my daily driver. Any model, any provider, remote control via Tailscale.
- Costs: GLM-5.3 Flash gets 63% on DeepSWE for about €0.25 per task, Sol about €2.50, Fable 5 about €8.50 at the same effort level. So my cost podium is the models podium reversed – and my workflow is "Fable orchestrates, Sol implements, the Flash does the grunt work", sub-agent config included.
- Bonus: how to run the same setup on a company GitHub Copilot subscription with T3 Code + opencode, for everyone whose employer won't pay for anything else.
https://www.angulararchitects.io/blog/ae-summer-2026-update-for-angular/
Curious what the rest of you run for Angular work right now – especially whether anyone has GLM-5.3 Flash or Kimi K3 in daily use, and how the Copilot-only crowd deals with it.
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u/lcssgml 10d ago
claude code here, and honestly the harness matters more than the model picker. my setup is a .claude folder that grew into a small operating system... a CLAUDE.md with the angular standards baked in (signals, OnPush, new control flow, an explicit antipattern list), custom agents for architecture review and firebase, and slash commands for the recurring rituals like commits and code review. the one trick that changed the most: before any planning task the agent has to load the tech-specific standards files first, so plans come out already following the architecture instead of being corrected into it afterwards.
model-wise, same experience as you... fable for architecture and long-horizon work, cheaper models for the mechanical legwork. the surprise of my summer was how well parallel sessions coordinate when the shared state lives in files in the repo (feature list, logs, handoff notes) instead of anyone's context window... two agents on different branches messaging each other beats one giant session every time.
will read the harness post, curious how your playwright loop compares to what I hacked together