Turn agents into leverage you can reason about, price, debug, and ship.

Models confabulate, lose context, ignore instructions, get slow, get expensive, and open security holes. We teach you to build for that reality and ship systems that survive contact with real users, real data, and real workflows.

Who is it for
audience.diff · 4 changes
mega/audience.md
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Mid-level and senior developers already working with agents like Cursor, Codex, Claude Code, OMP, or Pi.
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Someone who wants it expert to expert — no guru posture, no rented-Lambo promises, no ten magic prompts.
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Beginners.
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The AI-hesitant, or anyone shopping for shortcuts.
The journey · Programmer → MEGA developerThe journey · Programmer → MEGA developer
After MEGA you become the developer people trust when AI work demands judgment, engineering taste, and systems that actually ship. AI becomes a leverage layer you can reason about – and the work gets fun again.

01
Use agents to complete individual tasks
Code, tests, debugging, research

Direct prompting, synchronous work, manual verification

02
Understand and control how agents work
Model mechanics, context, inference, reasoning, limitations

Agent loops, state, memory, tools, sandboxes, permissions

03
Collaborate with agents to solve larger problems
Exploration, planning, implementation, review

Context shaping, model steering, informed judgment

04
Turn effective practices into repeatable systems
Skills, tools, integrations, memory

Reusable workflows, shared knowledge, verification loops

05
Own product outcomes, not just implementation
Frame problems, question requirements, understand business needs

Balance user value, quality, scope, risk, and engineering effort

06
Delegate complete outcomes with confidence
Features and end-to-end product workflows

Clear intent, constraints, evaluations, quality gates, accountability

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