EasySpecs Labs
Cut context waste and token burn without losing agent quality.
Your agents work — but every run ships the whole repo, token bills spike, and quality drops when context is trimmed wrong. In 1–2 days on your stack, engineer layered context, retrieval, compaction, and token budgets so agentic coding scales on cost and signal, not hope.
- €4,995
- 1–2 days
Business outcome
Merge quality holds while token spend drops — teams run agents with explicit context layers, measurable budgets, and retrieval that pulls the right facts instead of dumping everything into the prompt and praying.
What you leave with
- Layered context packs and scope rules checked into your repository
- Retrieval and compaction patterns tuned to your stack — not generic RAG slides
- Token budgets and run-cost baselines your team can enforce per agent workflow
- Quality-vs-cost tradeoff checklist for expanding or trimming context
- Observability starter — token, latency, and quality signals on real agent runs
- Context engineering playbook versioned next to the code for champions to roll out
Workshop curriculum
Context engineering & token optimization curriculum
Optimize block for teams past Scale — context design, retrieval, compaction, and token economics on your repository, not generic “prompt better” advice.
Context engineering at scale
Layered context packs, scope boundaries, and freshness rules — what agents should see, what stays out, and how context stays versioned next to the code when squads and models change.
Retrieval and signal density
Repo-native retrieval, MCP and graph-backed facts, and ranking so agents start from high-signal context — not a 200k-token paste of everything that might matter.
Token optimization and compaction
Budgets per run and per sprint, summarization and compaction patterns, cache-friendly context, and when to trade tokens for quality vs. cut cost without breaking merge bars.
Cost and quality observability
Measure tokens, latency, and diff quality together — dashboards and run logs leadership can review so “optimize context” is engineering, not folklore.
Team standards for context ROI
Shared playbooks for context pack ownership, review of context changes, and rollout so every squad inherits the same token discipline instead of private mega-prompts.
Key metrics
- Investment: €4,995 · 1–2 days · up to 15 participants
- Conservative payback: ~2 weeks when token waste and context rework drop
- Year 1 ROI (conservative): 10×–25× vs. workshop cost
- Delivery: on-site or remote · context artifacts land in your repository
When to use this program
When agents run org-wide after Build or Scale but token bills climb, runs are slow, or quality swings when someone “optimizes” context by guessing.
Conservative ROI scenario
Two weeks to pay back a €4,995 context engineering workshop
Conservative scenario: a team of eight engineers cuts 30–40% token spend on recurring agent runs while holding merge quality — plus hours reclaimed from context rebuilds and failed runs — covering €4,995 in roughly two weeks at typical loaded rates, then compounding each sprint.
Agentic Coding Coaching
Workshops are coached by senior EasySpecs practitioners — product, structured requirements, and platform architecture at the table with your team, not junior facilitators reading slides.
Xesca Alabart
Lead coach — product & requirements · CEO, EasySpecs
Xesca combines product leadership with requirements engineering, helping teams turn business intent into explicit objectives and acceptance signals agents can work against—not vague chat prompts. She facilitates mixed rooms of engineering, product, and design while keeping a sharp definition of what “done” means.
- Aligns engineering, product, and design without diluting technical depth
- Brings structured requirements practice into AI-assisted delivery
- Based in Barcelona; delivers in English, Spanish, or Catalan as needed
Carlos Guirao
Carlos Guirao Capistany
Lead coach — platform & agent workflows · CTO, EasySpecs
Carlos architects EasySpecs’ platform and AI systems with an emphasis on safe, reviewable change in mature codebases. He focuses on boundaries, APIs, and verification so agentic engineering produces diffs your team can trust—not opaque churn.
- Systems and integration architecture for complex products
- Hands-on with agent workflows, tools, and how they land in your repository
- Leads the technical spine behind Application Mapping and agent-ready context
FAQ
How is this different from the Development Team Workshop?
The dev workshop (€4,995) builds first agent loops and review rituals. Context Engineering & Token Optimization (also €4,995) assumes those basics exist — or equivalent experience — and goes deep on layered context, retrieval, compaction, and token economics.
How is this different from Control Plane at Scale?
Context engineering (€4,995) fixes what agents see and what each run costs. Control Plane (€7,995) adds org-wide orchestration, governance gates, and fleet monitoring. Most orgs run Control Plane in Scale first, then context engineering in Optimize when token burn is measurable org-wide.
Can we combine this with the dev workshop in one engagement?
Yes — some orgs book back-to-back blocks in one visit. More often they run the dev workshop in Build, Scale with control plane or embed, then context engineering once org-wide token pain is measurable on real runs.