AI coding state of play, Agile meets Architecture, March 10 2026
Overview of the current state of AI coding tools, and questions technical leaders should be asking themselves right now.
- Context engineering
- Increased autonomy, reduced supervision - ups and downs
- Harnesses
for your own work Help teams amplify the good, not the bad and the ugly Make it as safe as possible to use AI Use AI to improve and modernise the systems landscape
it's in ./app - Build system: Poetry - Remember to activate the virtual environment before any Python or Poetry command Simplest form: “Rules” files AGENTS.md
and conventions Skills Rules Specs Com- mands Context interfaces MCP Servers Tools Skills “Intelligentlyˮ loaded, just in time Manage and monitor context size
want to amplify? → Skills Workflows to build for modernisation initiatives? → Subagents, Skills Tools that should be available in your org? → CLIs, MCP servers, LSPs, … Versioning and distribution? Is it making things better, or worse? What are practices you want to amplify? → Skills
Impact …if AI gets something wrong Detectability …that AI got something wrong → Know the AI tool, know and engineer the context → Know your confidence level in the requirements → Know the use case criticality → Know your feedback loops Which workflow? How much review? How long without supervision?
of 2024 “Generating 100 lines of code only costs about 12 cents, compare that to a developer salary!ˮ Keynote at Craft Conf 2024 (simplified) Summer 2025 viberank.app
of 2024 “Generating 100 lines of code only costs about 12 cents, compare that to a developer salary!ˮ Keynote at Craft Conf 2024 (simplified) Summer 2025 viberank.app $20 Flat Rates $200 Flat Rates Request limiting
$2,50, not $0,12? Plan Review the plan Research existing code Implement the first task Make changes Run the tests Fix the tests Check lint errors Fix lint errors Check the browser “Itʼs not rendering, debugˮ Fix Code review Improve a method Summarise
sandbox coding agents? Does everybody understand the lethal trifecta? Where do you want to experiment with cloud agents? How do you help your teams gauge the appropriate level of supervision?
CPU Coding Agent Principles Rules, Examples Ref Docs How-tos CfRs Guides feed-forward Runtime state Static state Agent-as- judge Sensors Mutation testing feed-back self-correction CPU-executed when possible Shift sensors left Human Steering Loop Uses to build steering loop LSPs CLIs, scripts
the loop Where can your organisation give in to that pull, where is it dangerous? Context engineering Powerful lever of amplification – both good and bad