Observed Signal · Jun 16, 2026 · Thought Leadership · Source: DEV Community · Impact: 1/5 · Sentiment: Positive
Developer’s Practical Workflow for Working with AI Agents
Mitesh Sharma published a first‑person account on DEV Community (2026-06-16) describing how he uses AI agents in software development. He argues that planning, architecture and test strategy are now more important than hand-coding because agents can execute tasks quickly but will follow vague plans incorrectly. His workflow: design a clear plan, decompose work into small independent tickets, have an agent implement a ticket, use a different model to review the code, and require human review only for high‑risk changes. He stresses enforcing non‑negotiable rules (via hooks, CI checks or scripts) rather than relying on natural‑language instructions, documents architecture rules for agents to follow, and iteratively improves the surrounding “harness” (skills, guardrails, review workflows) to increase long‑term value.
Practical first‑person guidance on agentic development and governance is useful to engineering teams but does not introduce new platform releases, partnerships, or industry‑shifting policy changes.
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Key Takeaways & Evidence Grounding
- Article published on DEV Community on 2026-06-16.
- Author Mitesh Sharma describes a workflow: Plan → break into small tasks → create tickets → agent implements → different model reviews → humans review critical changes.
- Author recommends enforcing mandatory rules with deterministic mechanisms (hooks, scripts, CI checks) rather than relying solely on written instructions.
- Author reports using an architecture document to record system rules so agents follow consistent constraints.
- Author observed models can drift from instructions (example: an 'always use a git worktree' rule in AGENTS.md was occasionally ignored).
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