IIIMPACT Design

We're compiling code faster than trust.

AI amplifies software engineering experience. Seniors gain the most; juniors use more tokens with less results.

AI agents are the new jr. engineers/designers but they need guard rails.

Cap your daily agent output to what you can actually review and verify

Tech/Design debt is cheap to take care of with AI - so use it to clean up your product.

Right now it's too easy to let AI write the code or design the app while you skip the learning. The bug or problem gets fixed but your mental model doesn't move

Spend more time thinking and understanding as we are trading future capability for present-day speed, and these tools won't make us do otherwise.

From he age old saying - if you have 60 min to solve a problem, you should spend 50 min understanding the problem.

When Compute Costs More Than Headcount

We are officially seeing AI compute expenses actively outweigh the personnel costs they were supposed to replace.

The biggest mistake happening right now? Treating AI like a static SaaS license. AI is a variable expense. Poor usage governance recently cost one enterprise $500M in a single month because they didn't cap employee access...but hey you all have to move faster and use "more AI".

The token costs for running AI agents are now exceeding what they were paying the employees they fired.

When the tokens run out, the AI stops. Just stops. No continuity. No workaround. Just a spinning wheel where your workforce used to be.

You fired humans to save money and bought a subscription that bills you into a corner.

The employees you let go knew what to do when things broke.

The tech industry is walking blindly into a massive pricing vulnerability with AI coding tools.

Developers are rapidly transitioning from writing code to prompting it. As a result, engineering teams are losing their native familiarity with their own software architecture. They are becoming entirely dependent on external AI models to generate, debug, and maintain their codebases.

Uber blew through a 12-month AI budget in exactly four months.

Microsoft watched API costs climb and forced its own engineers to abandon Anthropic's Claude Code, despite those engineers preferring it over Copilot.

If AI providers execute a rug pull and raise token prices, engineering teams will be fuct. They cannot simply revert to writing and maintaining the code manually.

The developers will have already lost the deep institutional knowledge required to navigate their own systems natively.

When your team relies entirely on an external AI model to maintain your product, you are no longer paying for a software tool. You are paying rent on your own codebase.

The AI landlords WILL raise token prices because they need to appease shareholders when they go public.

When this happens, and you've let go a significant portion of your team that had institutional knowledge, you competitors that retained their experienced teams with proper AI governance... they will be able to surpass your overworked, short-staffed design/dev teams with ADHD trying to manage 5 agents to just keep up.