Search a title or topic

Over 20 million podcasts, powered by 

Player FM logo
Artwork

Content provided by Thanos Diacakis, Michael Rollins, Thanos Diacakis, and Michael Rollins. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Thanos Diacakis, Michael Rollins, Thanos Diacakis, and Michael Rollins or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Player FM - Podcast App
Go offline with the Player FM app!

Taming AI Context Chaos: How Epic Scale AI Ships Faster with MCP

48:43
 
Share
 

Manage episode 517804865 series 3634366
Content provided by Thanos Diacakis, Michael Rollins, Thanos Diacakis, and Michael Rollins. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Thanos Diacakis, Michael Rollins, Thanos Diacakis, and Michael Rollins or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

00:00 Cold open: “Humans of Earth” intro 00:38 Meet the guest: Colin Masters (Epic Scale AI) 02:40 Colin’s origin story (military → construction → NYSE → dev) 04:00 The EPIC method: Explore–Plan–Implement–Check 05:40 Context isn’t a dump: vector DB + forced session search 06:20 Plans = branches (GitHub issues integration) 07:10 Memory bank: standardize decisions (deposits vs withdrawals) 08:40 Feedback to feature: free tier shipped in 3 hours 10:00 Shared vs project context; 30 MCP tools 11:10 Using AI since 2024; choose simple over complex 12:20 Explore phase prompts → define a shippable MVP 13:10 AI-first ops: branches, artifacts, and shared context 14:20 Context bloat and model limits 15:05 The Claude 4.5 rant (pain points) 16:10 Buy vs build: why consider Epic Scale 17:10 Why “last 20 commits” isn’t enough 18:00 Semantic tasks and progress tracking 19:10 Watching cross-branch changes 20:00 Agent loops—with human review 21:00 Human-in-command: no auto-approve 22:10 Quote: “Developers in control of their tools will succeed.” 23:40 Houses vs software: constraints and collaboration 29:10 Where Epic Scale shines (small teams 10) 32:00 Status without Big‑A Agile: stakeholder visibility 34:10 Failing as a learning loop 38:10 Mindset shift: embrace AI or get left behind 39:20 Where AI beats humans (YAML, cross-file reasoning) 41:10 Juniors are crushing it; Go‑to‑Market Engineer 44:00 Speed breaks sales/support; training new grads 47:00 Where to find Epic Scale + free tier note 47:40 OutroAI dev isn’t “dump more into the context window.” Colin Masters from Epic Scale AI breaks down how the EPIC method (Explore–Plan–Implement–Check), an MCP server, and a shared vector memory turn chaos into shipping velocity—especially for small, AI‑first teams.We get practical about plans-as-branches with GitHub issues, memory banks to stop re‑deciding decisions, why auto‑approve wrecks projects, and how a user comment led to a free tier in three hours. We also debate “houses vs software,” the rise of the Go‑to‑Market Engineer, and what juniors are getting right with AI.Recorded: October 14, 2025What you’ll learn:How to replace “tickets” with plans-as-branches and keep context cleanWhy vector DB + retrieval beats giant context windowsGuardrails for agent loops (human-in-command, no auto‑approve)Where AI truly outperforms humans (cross-file reasoning, YAML, refactors)Team shape for AI‑first orgs (small, sharp, 10)How to create stakeholder visibility without Big‑A Agile ceremonyGuestColin Masters — Epic Scale AI: https://epicscale.ai/Chapters See chapter markers above.Subscribe for more on AI engineering, MCP, and practical agent workflows.Hashtags: #AIEngineering #MCP #DevTools #AIFirst #VectorDB #VSCode #GitHub

  continue reading

28 episodes

Artwork
iconShare
 
Manage episode 517804865 series 3634366
Content provided by Thanos Diacakis, Michael Rollins, Thanos Diacakis, and Michael Rollins. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Thanos Diacakis, Michael Rollins, Thanos Diacakis, and Michael Rollins or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

00:00 Cold open: “Humans of Earth” intro 00:38 Meet the guest: Colin Masters (Epic Scale AI) 02:40 Colin’s origin story (military → construction → NYSE → dev) 04:00 The EPIC method: Explore–Plan–Implement–Check 05:40 Context isn’t a dump: vector DB + forced session search 06:20 Plans = branches (GitHub issues integration) 07:10 Memory bank: standardize decisions (deposits vs withdrawals) 08:40 Feedback to feature: free tier shipped in 3 hours 10:00 Shared vs project context; 30 MCP tools 11:10 Using AI since 2024; choose simple over complex 12:20 Explore phase prompts → define a shippable MVP 13:10 AI-first ops: branches, artifacts, and shared context 14:20 Context bloat and model limits 15:05 The Claude 4.5 rant (pain points) 16:10 Buy vs build: why consider Epic Scale 17:10 Why “last 20 commits” isn’t enough 18:00 Semantic tasks and progress tracking 19:10 Watching cross-branch changes 20:00 Agent loops—with human review 21:00 Human-in-command: no auto-approve 22:10 Quote: “Developers in control of their tools will succeed.” 23:40 Houses vs software: constraints and collaboration 29:10 Where Epic Scale shines (small teams 10) 32:00 Status without Big‑A Agile: stakeholder visibility 34:10 Failing as a learning loop 38:10 Mindset shift: embrace AI or get left behind 39:20 Where AI beats humans (YAML, cross-file reasoning) 41:10 Juniors are crushing it; Go‑to‑Market Engineer 44:00 Speed breaks sales/support; training new grads 47:00 Where to find Epic Scale + free tier note 47:40 OutroAI dev isn’t “dump more into the context window.” Colin Masters from Epic Scale AI breaks down how the EPIC method (Explore–Plan–Implement–Check), an MCP server, and a shared vector memory turn chaos into shipping velocity—especially for small, AI‑first teams.We get practical about plans-as-branches with GitHub issues, memory banks to stop re‑deciding decisions, why auto‑approve wrecks projects, and how a user comment led to a free tier in three hours. We also debate “houses vs software,” the rise of the Go‑to‑Market Engineer, and what juniors are getting right with AI.Recorded: October 14, 2025What you’ll learn:How to replace “tickets” with plans-as-branches and keep context cleanWhy vector DB + retrieval beats giant context windowsGuardrails for agent loops (human-in-command, no auto‑approve)Where AI truly outperforms humans (cross-file reasoning, YAML, refactors)Team shape for AI‑first orgs (small, sharp, 10)How to create stakeholder visibility without Big‑A Agile ceremonyGuestColin Masters — Epic Scale AI: https://epicscale.ai/Chapters See chapter markers above.Subscribe for more on AI engineering, MCP, and practical agent workflows.Hashtags: #AIEngineering #MCP #DevTools #AIFirst #VectorDB #VSCode #GitHub

  continue reading

28 episodes

All episodes

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Copyright 2025 | Privacy Policy | Terms of Service | | Copyright
Listen to this show while you explore
Play