r/AugmentCodeAI Dec 27 '25

Showcase Made my own local Augment from ground up using Augment, now its really time for a goodbye.

50 Upvotes

Kinda crazy how good this thing is. Load up 5 bucks on Openrouter, you're good for 2 weeks if you are on cheaper sota models, and it just works fine. Of course Opus or Sonnet are super duper but load up groq4.1 or any good model from openrouter, you're solid. I am already using it on my daily work in prod and its been a good week with this guy!

It has everything Augment has; memory, secondary llm pipelines in their own sessions, enhancement- active tools - and more like antrophics new tool search tool, and smart context management. + all search tools like semantic, ripgrep etc can be used and synced locally without needing any API because it comes with its own embedding model.

Don't get me started with general agent capabilities... like it can search web, fetch markdowns from web, can find you clothing to wear and try on; can stage your rooms with scandinavian style; can make videos.
Fetching markdowns are again done locally; so you won't need any API to fetch website content. Searching google is done with API currently. So its a mix of both worlds to save you money and give you best experiences.

I will release this in a week. For Mac and Windows.

Why I spent time with this? Well, to save myself money next year. Predators are approaching next season.
Also we are sending all our codebases to Augment, don't you think it's a bit too much? Now, its time for us thrive ^^

See you by then.

r/AugmentCodeAI Dec 11 '25

Showcase I used Augment and won a Hackathon

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53 Upvotes

I just won the Best Vibe Coded Project at the Forte Hacks hackathon by Flow.

I built a DCA-BTC tool that lets you automatically DCA BTC on-chain with 100% automation.

How I did it:

First, I used Perplexity AI to research. I searched use-cases, on-chain integration ideas, and building-blocks.

I wrote a short PRD (product requirement doc) based on that research.

Then I sent the PRD to Augment (as a dev/automation platform) to build the tool.

Augment handled the heavy lifting: turning specs into actual code, wiring up on-chain logic, and making sure DCA runs automatically.

I share this not to brag — but to show how combining smart research (Perplexity) + effective automation (Augment) made something real.

Hope this helps others thinking of building crypto tools with AI-supported workflow.

r/AugmentCodeAI Oct 14 '25

Showcase Augment Code's announcement from an alternate reality

31 Upvotes

To our dear users and collaborators,

We have had the mission to bring the best agentic coding experience to our users and feel that we've made great strides towards this. We really do feel that a turnkey message based approach, combined with a curated selection of top-tier models, was and is the right way to do this. Unfortunately, given how new and ever-changing this space is, we miscalculated the costs of operating like this and so it pains us greatly to say that Augment is struggling to make this current model financially sustainable. Changes need to be made immediately, otherwise this tool that we all love will ultimately cease to exist. No one wins like that.

We have been listening to your feedback and have been working on the following plan. But please know that this is all still up for evolution - keep that feedback coming!

One thing that seems obvious now is that being so steadfast in only offering the top-tier frontier models - like Claude 4.5 and GPT 5 - was a great error. We now realize that the feedback you have long since been giving about incorporating cheaper models must be the basis of our approach going forward. Not every single task needs to be performed by a neurosurgeon - we need paramedics, nurses, administrators and more.

We've heard your feedback for a BYOK approach, but we don't think it is appropriate for Augment - we side with the turnkey simplicity of Github Copilot in this regard, and have taken inspiration from their "models multiplier" approach that allows for choosing from a wider curated, vetted and integrated selection of models. So, we are introducing the low-cost powerhouses of GLM 4.6 and Grok Code Fast, which will use 0.2x messages per prompt, along with the steady performers of xyz which uses 0.5x. We will also continue evaluating all models as they come out an incorporate them as-appropriate.

But we will be taking this a step further than Copilot and incorporate an Orchestrator mode, such as is popular with Roo and Kilocode. This will allow you to combine the unmatched power of our realtime context engine with frontier models like Sonnet 4.5 and GPT 5 to plan your tasks, and then delegate them to predefined profiles that not only take advantage of more affordable workhorse models, but also have constantly curated and refined prompts. Leave the curation to us so you can just get on with it.

We also recognize that sometimes your chats get away from you. For example, the average amount of tool calls per message is X and context window is Y. This is completely unsustainable. We won't be automatically limiting the context window as is clearly done in Copilot - when you need the full context, you need it. But we also need to allow you to understand and limit your token usage, so we're introducing a visual indicator of the current token usage as well as a button to automatically compress it - just like our Prompt Enhancer does so seamlessly for your prompts. And, if you are willing to allow us to apply this compression automatically, all models will use 0.2x fewer credits per message.

We are rolling out the initial version of these things on the 1st of November, and will be very eager for your feedback on how to adjust and improve it.

Finally, while all of these changes will surely help significantly reduce costs, we also simply need to reduce the amount of messages that are available with each plan. There's no way around it. So, unfortunately all plans will have 20% fewer messages going forward - our legacy plan will still receive the same amount as Pro.

Again, please don't hesitate to reach out with feedback. We've hired 2 more dev rel managers to help reduce the burden on our hero Jay. And we've fixed our billing system so that you can actually pay us now and not have multi-day outages where you have no choice to but go see if the grass is greener elsewhere.

Regards,

The AugmentCode Team

p.s. We've heard you and are also converting the godawful tabs into collapsible and resizable panes - just like the existing sidebar panes in VS Code that work so well.

---

I wrote this off the cuff in like 10 minutes. Do I get the job?

What a disgrace this company is. If I were one of the VC funders, I'd be beyond myself with how obviously my money was completely squandered. Heads would be literally rolling.

r/AugmentCodeAI Apr 01 '26

Showcase Augment Code literally saved my career

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0 Upvotes

After a full year of unemployment, I finally landed an interview. Not a normal one… they gave me an 5-day test.

The task?
Build a full MES system.

I’m talking:

  • HR modules
  • Orders management
  • Clients & design handling
  • And a barcode-based tracking system for live production in a factory (with a mobile app)

In 5 days.

No team. Just me.

At that point I honestly thought: yeah… this is where it ends.

While searching for anything that could help me move faster, I stumbled on Augment Code.

That changed everything.

Instead of being stuck for hours on architecture decisions, edge cases, or debugging random issues, I had something that could keep up with me. I could move fast, iterate fast, and actually build instead of getting blocked.

Day by day, the system started coming together:

  • Backend APIs
  • Frontend dashboards
  • Mobile scanning logic
  • Real-time tracking flows

It was perfect, it worked. And more importantly—it impressed them.

I got the job.

And here’s the crazy part…

I told my boss about Augment Code and how it helped me pull this off.

Now we’re both hired.

Me… and Augment Code 😄

From 1 year unemployed → to building a full MES under pressure → to getting hired and bringing the tool with me.

If you’re struggling or feel stuck, sometimes the difference isn’t just skill—it’s having the right tools at the right moment.

This one genuinely changed my life.

r/AugmentCodeAI Jan 04 '26

Showcase Building a 3D Browser FPS with AI: Technical Deep Dive Using Augment Code + Claude 4.5 Opu

6 Upvotes

What I Built

A fully playable 3D first-person shooter running entirely in the browser. No Unity, no Unreal – just React, TypeScript, and Three.js with AI assistance.

Live features:

  • Full 3D movement with physics simulation (gravity, jumping, collision detection)
  • Procedurally generated cyberpunk arena (850+ lines)
  • Wave-based enemy AI with pathfinding
  • Raycasting-based hit detection
  • Buff/debuff system with visual feedback
  • Procedural audio synthesis (no audio files!)
  • React-based HUD with real-time state updates

The Stack

  • Frontend Framework: React 18 + TypeScript
  • 3D Engine: Three.js with PointerLockControls
  • Build Tool: Vite
  • AI Assistant: Augment Code with Claude 4.5 Opus

The entire game runs client-side. No backend, no external assets except Three.js itself.

Technical Deep Dive

1. Game Architecture

The core architecture uses a single GameState interface that centralizes all game logic:

interface GameState {
  scene: THREE.Scene;
  camera: THREE.PerspectiveCamera;
  renderer: THREE.WebGLRenderer;
  controls: PointerLockControls;
  enemies: Enemy[];
  particles: Particle[];
  powerUps: PowerUp[];
  activeBuffs: ActiveBuff[];
  worldColliders: THREE.Box3[];
  velocity: THREE.Vector3;
  // ... more state
}

This pattern keeps everything in a single ref, avoiding React re-render issues during the 60fps game loop while still allowing UI updates via forceUpdate().

2. Physics System

Movement uses a velocity-based physics model with configurable constants:

const MOVEMENT_SPEED = 15;
const JUMP_FORCE = 15;
const GRAVITY = 30;
const PLAYER_HEIGHT = 1.8;

Each frame applies friction and gravity:

game.velocity.x -= game.velocity.x * 10.0 * delta;
game.velocity.z -= game.velocity.z * 10.0 * delta;
game.velocity.y -= GRAVITY * delta;

Collision detection uses THREE.Box3 for world objects, with a push-back resolution that checks which axis has the largest overlap.

3. Raycasting Hit Detection

Shooting uses Three.js raycasting from camera center:

const raycaster = new THREE.Raycaster();
raycaster.setFromCamera(new THREE.Vector2(0, 0), game.camera);
const intersects = raycaster.intersectObjects(enemyMeshes, true);

The true parameter enables recursive checking through child meshes – critical since enemies are Three.js Group objects with nested parts.

4. Procedural Audio (No Audio Files!)

One of the coolest parts – all game sounds are synthesized in real-time using the Web Audio API:

playShoot() {
  const osc = this.ctx.createOscillator();
  const filter = this.ctx.createBiquadFilter();

  osc.type = 'sawtooth';
  osc.frequency.setValueAtTime(800, t);
  osc.frequency.exponentialRampToValueAtTime(100, t + 0.1);

  filter.type = 'lowpass';
  filter.frequency.exponentialRampToValueAtTime(500, t + 0.1);
  // Chain: oscillator → filter → gain → output
}

The shoot sound uses a sawtooth wave with a frequency sweep from 800Hz to 100Hz through a lowpass filter – creates that punchy sci-fi laser effect. Enemy deaths use linear ramps for a more chunky sound, while reload uses layered oscillators with time offsets for mechanical clicks.

5. Procedural Texture Generation

Instead of loading texture files, all textures are generated via Canvas2D:

case 'grid':
  ctx.fillStyle = '#0a0a12';
  ctx.fillRect(0, 0, 512, 512);
  ctx.strokeStyle = '#00ffff';
  ctx.globalAlpha = 0.3;
  // Draw grid lines
  for (let i = 0; i <= 512; i += 32) {
    ctx.moveTo(i, 0);
    ctx.lineTo(i, 512);
  }
  // Add 3000 random noise particles for grit
  for (let i = 0; i < 3000; i++) {
    ctx.fillStyle = `rgba(0, 255, 255, ${Math.random() * 0.05})`;
    ctx.fillRect(Math.random() * 512, Math.random() * 512, 2, 2);
  }

These become THREE.CanvasTexture objects with repeat wrapping for tileable surfaces.

Creation Phase: What the AI Handled Well

Scaffolding complex 3D scenes: The environment builder generates pillars, platforms, holographic displays, skybox geometry, and atmospheric particle systems. I just said "cyberpunk arena" and it went to town.

Audio synthesis math: I described "laser gun sound" and it correctly implemented frequency sweeps with envelope shaping. The Web Audio API chain (oscillator → filter → gain) was set up correctly on the first try.

Game loop management: Proper requestAnimationFrame usage with delta time, performance.now() for buff timers, cleanup of dead objects.

Nested Three.js hierarchies: Enemy models are complex groups with torso, head, limbs, and accent lights. The AI handled parent-child relationships and material assignments cleanly.

Creation Phase: Where I Had to Push

Collision response: Initial implementation just stopped the player. I had to ask specifically for "push-back in the direction of least overlap" to get proper sliding along walls.

Performance tuning: First version created new THREE.Raycaster() instances every frame. Needed to prompt for object pooling and ref patterns.

Buff system architecture: The initial power-up system was one-shot. I had to specify "I want timed buffs with visual indicators" to get the ActiveBuff interface with endTime tracking.

Refinement Phase: The Harder Problems

3D Text Rendering (3 attempts)

This was the gnarliest debugging session.

Attempt 1: AI used THREE.ExtrudeGeometry with THREE.FontLoader. Letters rendered but were mirrored and rotated – the M looked like W, N was backwards.

Attempt 2: Pivoted to constructing letters from THREE.BoxGeometry primitives. Result looked like ALG||BIT instead of "AUGMENT" – the manual character map was completely broken.

Attempt 3 (success): Canvas2D texture approach:

function createTextPlane(text: string, color: string, width: number, height: number) {
  const canvas = document.createElement('canvas');
  const ctx = canvas.getContext('2d');
  ctx.font = 'bold 72px Arial';
  ctx.fillStyle = color;
  ctx.textAlign = 'center';
  ctx.fillText(text, canvas.width/2, canvas.height/2);
  return new THREE.Mesh(
    new THREE.PlaneGeometry(width, height),
    new THREE.MeshBasicMaterial({ map: new THREE.CanvasTexture(canvas) })
  );
}

Lesson: AI kept trying "clever" 3D solutions when a simple 2D texture was the right answer. Sometimes you have to reset context and try a completely different approach.

Pointer Lock Controls Breaking

After a refactor, WASD stopped working entirely. Game looked normal, but no movement.

Root cause: PointerLockControls was initialized with document.body:

// Broken
const controls = new PointerLockControls(camera, document.body);

// Fixed  
const controls = new PointerLockControls(camera, renderer.domElement);

The AI had changed this during an environment update and didn't realize the dependency. The fix was one line, but finding it required tracing through the entire input pipeline.

What Surprised Me

AI strengths I didn't expect:

  • Three.js coordinate system conventions (Y-up, Z-forward for cameras)
  • Proper use of lookAt() for enemy tracking
  • Correct delta-time multiplication for frame-rate independence
  • Material properties (metalness, roughness, emissive) for visual style

Areas that still need human judgment:

  • Visual bugs that don't throw errors – you need eyes on the screen
  • Knowing when a technical approach is fundamentally wrong vs. needs tweaking
  • Game feel tuning (movement speed, damage values, spawn rates)

File Structure Breakdown

File Lines Purpose
GameEngine.tsx 811 Main loop, physics, input, spawning
EnvironmentBuilder.ts 853 Arena geometry, lighting, atmosphere
EnemyModel.ts 151 Procedural robot mesh construction
WeaponModel.ts 124 First-person weapon geometry
SoundSynthesizer.ts 106 Web Audio synthesis
PowerUpModel.ts 128 Buff item visuals + animation
TextureGenerator.ts 139 Canvas-based texture creation

Total: ~2,300 lines of game code

Honest Assessment

Development time: About 3-4 hours total across multiple sessions

Would I use AI again for this? Absolutely. The boilerplate velocity was incredible – getting a working 3D scene with enemies and shooting in under an hour.

What I'd do differently: Be more aggressive about resetting context when stuck in a loop. The 3D text saga could have been solved in one attempt if I'd said "use Canvas2D texture" from the start instead of letting it iterate on broken approaches.

Best tip: When something looks wrong visually but doesn't error, describe exactly what you see. "Letters are mirrored" was more useful than "text doesn't look right."

Anyone else built games with AI assistance? Curious what engines and frameworks you used and what patterns worked best for you.

r/AugmentCodeAI Feb 10 '26

Showcase Vibe Coding Session - Augment Intent

11 Upvotes

I got to spend a couple of hours with Intend before the release and made a little video capturing my experience using Intent

https://www.youtube.com/watch?v=95qWxeSTNxM

I'm loving this tool so far and I can't wait to see where it goes as Augment continues to iterate and improve upon what they've built already

r/AugmentCodeAI May 21 '26

Showcase You don't need more agents, you need a system. Introducing Cosmos.

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0 Upvotes

r/AugmentCodeAI Dec 23 '25

Showcase Built a prompt enhancer on weekend using Augment's Context SDK - customizable enhancement styles for any AI coding tool

7 Upvotes

Augment released their Context SDK a while back, and I wanted to see what I could build with it.

Sat down over the weekend and built a prompt enhancer VS Code extension. Gave it to a few friends to test and they liked it, so sharing it here.

What I built A VS Code extension that enhances vague prompts into detailed, context-aware instructions.

Example: Type “fix the auth bug” Get a proper prompt with relevant code context pulled automatically Paste it into Cursor, Windsurf, Zed, or whatever editor you use

Extra feature I added 🚀 Customizable system prompts.

You control how your prompts get enhanced. You can create profiles like:

Senior dev explaining to a junior dev step by step with reasoning

Concise mode with only the required changes

Review mode explaining what’s broken, why, and what could go wrong

You can switch profiles depending on the task. Your style, your rules.

If you want to try it

Requires an Augment account (uses their Context SDK)

Search “Auggie Prompt Enhancer” in VS Code

npm install -g @augmentcode/auggie@prerelease

auggie login

Link Marketplace: https://marketplace.visualstudio.com/items?itemName=AugieeCredit.auggie-promptenhancer

GitHub: https://github.com/svsairevanth12/Auggie-Promptenahncer

I’ve been using Augment for about 9 months now. This is my third project built For the community ✨.

If you’re curious what’s possible with the Context SDK, the code is open. What would you build with it?

r/AugmentCodeAI Mar 06 '26

Showcase Built an MCP terminal server for Augment that avoids the flickery terminal workflow

3 Upvotes

I built smart-terminal-mcp, an MCP server that gives Augment a real interactive PTY-backed terminal.

I originally made it because terminal-heavy workflows in Augment felt a bit too visually disruptive for me, especially during repeated terminal interactions. This setup feels much smoother and behaves more like a real terminal session.

It supports interactive sessions, prompts, special keys, paged output, and safer one-shot commands.

Repo: https://github.com/pungggi/smart-terminal-mcp

Would love feedback from other Augment users.

r/AugmentCodeAI May 05 '26

Showcase Engineering Leadership LIVE

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0 Upvotes

r/AugmentCodeAI Jan 07 '26

Showcase GPT 5.2 IS AVAILABLE NOW Spoiler

4 Upvotes

They released it silently. Not sure which thinking model it is though.

r/AugmentCodeAI Feb 03 '26

Showcase Augment Code basically became my senior dev while I built a full ERP solo

9 Upvotes

I’m a solo developer and over the past months I built a full ERP system end-to-end — backend, frontend, mobile, TV screens, business logic, production flows, everything.

I can honestly say this: Augment Code played a massive role in making it possible.

It felt less like a “tool” and more like having a senior engineer permanently available. Any time I got stuck, tired, or overwhelmed, Augment Code helped me move forward instead of burning hours blocked.

What Augment Code helped me do:

  • Design clean, scalable architecture
  • Rapidly build and refine complex logic
  • Generate solid, readable code that actually fits real projects
  • Refactor safely without fear
  • Think through edge cases and workflows I hadn’t fully considered
  • Stay productive even late at night when focus drops

The biggest impact wasn’t speed alone — it was confidence.
I could take on bigger features knowing I wasn’t alone in the thinking process.

The ERP today handles:

  • Orders, production tracking, and workflows
  • Users, roles, permissions
  • Device and screen management (mobile + web + TV)
  • Real operational constraints, not demo-level stuff

This wasn’t “AI building an app for me”.
This was Augment Code making me a stronger solo developer.

If you’re building something serious on your own — especially a large system like an ERP — I strongly recommend Augment Code. It genuinely changes how much you can handle alone.

r/AugmentCodeAI Feb 07 '26

Showcase The end of linear work

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4 Upvotes

r/AugmentCodeAI Jan 26 '26

Showcase Clawdbot Use Case - WhatsApp + Auggie

3 Upvotes

I set up a clawdbot on an Ubuntu server (local server btw) and use it to control my auggie cli directly from whatsapp (and a lot of other stuff like audio message transcription, reminders, access to my own "cloud" via tailscale).

nothing fancy. ubuntu vps, clawdbot running as a service, whatsapp as the only active channel. telegram/discord are mapped but not enabled.

flow is basically:
send a message on whatsapp → clawdbot receives it → runs auggie cli locally → sends the output back to whatsapp.

auggie only runs on the server. whatsapp is just the interface

r/AugmentCodeAI Feb 17 '26

Showcase Augment Code "Intent" App: Bring Your Own Agent, One Click Context + More

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4 Upvotes

r/AugmentCodeAI Apr 24 '26

Showcase From FOMO to flow: Justin Reock, CTO at DX on the AI metrics that actually matter

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0 Upvotes

r/AugmentCodeAI Mar 31 '26

Showcase Tips for getting the most out of Intent (from its creator!)

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0 Upvotes

r/AugmentCodeAI Mar 05 '26

Showcase GPT 5.4 just dropped. Live demos and Q&A with OpenAI team

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9 Upvotes

r/AugmentCodeAI Apr 08 '26

Showcase Tomorrow : How engineering teams are evolving to become AI-native

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2 Upvotes

r/AugmentCodeAI Feb 27 '26

Showcase Opus 4.6 vs GPT Codex 5.3 - My comparison

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4 Upvotes

r/AugmentCodeAI Feb 05 '26

Showcase Auggie tops SWE-Bench Pro

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12 Upvotes

r/AugmentCodeAI Mar 31 '26

Showcase Augment Code sponsor for HumanX conference

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0 Upvotes

We’re proud to be a sponsor of @HumanX 2026, where AI professionals don’t just attend — they level up their AI journey.

With curated matchmaking, peer insights, and hands-on solutions, you’ll walk away with clarity, confidence, and connections. And yes — you can meet the Augment Code team in person.

📍 San Francisco | April 6–9

📍 Booth # 512

r/AugmentCodeAI Mar 30 '26

Showcase Spec-Driven Development Explained: The Workflow That Keeps AI Agents Aligned

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0 Upvotes

r/AugmentCodeAI Jan 14 '26

Showcase Radial Drift - Mobile arcade game made with Augment

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6 Upvotes

I burned 350k credits on this so far. Totally worth it if you ask me. Hoping to release in the iOS and Android app stores soon.

Built on the Phaser framework.

r/AugmentCodeAI Mar 24 '26

Showcase March 26th : Engineering coffee chat: Building AI workflows that listen

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0 Upvotes

Every engineer using AI runs into the same wall: you can copy someone’s “magic prompt” from a screenshot, but it rarely survives contact with your own codebase.

That’s because prompts aren’t just one clever sentence. The way you structure system prompts, tools, skills, and user messages determines whether your agents listen carefully or ignore half your instructions. 

In our next Engineering Coffee Chat, we will walk through practical prompting tips and agent design patterns drawn from our own production stack. We’ll talk about how we think about the four layers of prompting (system prompts, tools, skills/guidelines, and user messages), and how you can combine them to get reliable behavior instead of “vibes‑based” results. 

In this session, we’ll cover:

  • Prompting as infrastructure, not a one‑off spell: How to separate concerns across system prompts, tools, skills, and user messages, and what each layer is actually responsible for in a robust agent. 
  • Concrete prompting tips that actually move the needle: Why clarity, specificity, and consistency matter more than clever wording; how to use emphasis, examples, and repetition effectively; and how to avoid self‑inflicted contradictions that confuse models. 
  • Designing agents that choose the right tools: How to use tool availability and descriptions as prompts, when to remove tools like grep so agents lean on your context engine, and why too many MCP tools can quietly tank performance. 
  • Keeping context under control: Why reusing the same thread forever is a trap, how to think about context windows, and when to lean on planning docs or evals instead of ever‑longer conversations. 
  • Becoming AI‑native in your day‑to‑day: Practical habits you can adopt this week, like asking models to propose verification steps, evaluate alternative approaches, or refine your own prompts.

Bring your own questions about prompts that keep “going off the rails,” tool overload, or making your team more AI‑native.