Agentic workflows end-to-end.
How Jahnel Group wired an AI collaborator into every phase of the software development lifecycle — a structured ecosystem of agents, skills, commands, and safety hooks that turns planning docs into tested, production-ready pull requests.
A development lifecycle that tests itself — one ticket at a time.
Enterprise scope, two developers.
A multi-tenant SaaS platform carried 42 feature epics, 40+ architecture decision records, and 100+ interlinked planning documents — historically the work of a four-person team.
The mandate was to deliver full-scope enterprise software without diluting requirements rigor, architectural consistency, or security — and to do it at a pace the old process could not match.
One tool per concern.
Rather than AI as autocomplete, the team built a structured ecosystem — agents, skills, commands, and pre/post-tool safety hooks, one per concern — spanning discovery through deployment.
Planning docs are the prompt: the AI reads the same specs the humans wrote. Hooks enforce non-negotiable rules as code, and every correction compounds into a permanent, team-shared skill.
One ecosystem, six phases — agents at every step.
Discovery through deployment, with a purpose-built agent, command, or hook at each hand-off.
Requirements in Hours
Business-analyst, brainstormer, and griller agents draft epic requirements and stress-test approaches; meeting notes ingest straight into the planning repo.
One Canonical Model
Impact-analyzer and consistency-check agents keep entities, enums, and permissions aligned across 100+ docs, then translate specs into schema and controller stubs.
Epic → Stories → JIRA
Epics decompose into role-scoped stories with acceptance criteria and point guidance, created directly in JIRA and linked to the parent — no manual data entry.
Plan In, PR Out
Every ticket runs /plan then /implement — a strict vertical-slice loop: one failing test, minimal code to pass, refactor, next behavior.
RALPH for Patterns
Once a pattern is proven interactively three times, the RALPH loop automates the rest — build/test/lint gates, commit, fresh context; reviewed every 5–10 iterations.
Six Agents in Parallel
A PR fans out to six agents — correctness, security, tenancy, performance, test quality, and structure — deduplicated and re-verified against the actual code.
Docs That Self-Sync
Domain-sync and propagate keep planning docs aligned with the codebase; ADRs and runbooks publish to the wiki automatically — no silent drift.
Rules as Code
Pre/post-tool hooks block dangerous commands, unguarded controllers, and edits to accepted ADRs — the AI cannot take a non-compliant action even if told to.
Production velocity, measurable from day one.
A team of four, reduced to two.
A small team ships full-scope enterprise software — 42 epics, 40+ ADRs — at the pace that previously required a four-person team.
Review that never sleeps.
Six-agent parallel review replaces blocked peer review and adds security and tenancy dimensions human reviews routinely miss.
Every correction sticks.
A shared lessons log promotes repeated fixes into permanent skills and rules — the system measurably improves with every ticket shipped.
The full agentic toolchain behind the engagement.
AI & Agents
Commands & Skills
Loops & Hooks
Build & Delivery
Built to ship at
agent speed.
Jahnel Group runs AI-native engagements — built for teams who want to ship at agent speed.