WORKFLOW REVIEW
A day or two inside how your product and engineering team actually works — where AI is creating leverage, and where it’s creating drag.
1–2 DAYSMOST PRODUCT TEAMS STILL OPERATE AS IF AI DIDN'T EXIST*
*The teams that moved past it didn’t get faster. They rebuilt how products get built.
01
THE SHIFT
Most product organisations still run on assumptions formed before AI changed the cost of investigation, prototyping, and technical discovery. Discovery is slow. Prototypes are expensive. Engineering and product run on separate timelines — documents and tickets in between.
The teams that have re-tooled aren’t running the same playbook faster. They’ve rebuilt the loop. Investigation happens directly against the system. Prototypes get built in hours. Product managers interrogate code paths themselves. The friction between engineering and product collapses.
A year ago, most technical feasibility questions still required engineering cycles. Today many can be answered directly — through AI-assisted investigation against the codebase itself.
WEEKS→HRSPROTOTYPE CYCLE
ZEROTICKETS BETWEEN QUESTION & ANSWER
ONE LOOPPRODUCT + ENGINEERING
02
THE QUESTIONS
The shift surfaces questions most leadership teams haven’t had to answer before. Not tooling questions — operating-model questions.
- Q.1Where does AI actually change the work — versus add noise?→
- Q.2What does the PM / engineering boundary look like when PMs can prototype?→
- Q.3How do you hold technical quality when cycles collapse from weeks to hours?→
- Q.4What’s the right rhythm for discovery, decision, and shipping?→
- Q.5What do you do when the engineering team doesn’t want to change?→
03
THE WORK
These questions aren’t theoretical for me — they’re what I work through at Antare every day, alongside the engineering managers and product leaders I advise. It usually takes one of three shapes.
OPERATING REVIEW
Decision velocity, prototype loops, the PM/engineering boundary, discovery workflows. Ends in a written diagnosis and a small set of interventions.
DEEP DIVEONGOING ADVISORY
Selective, a few hours a month — for founders, engineering, and product teams navigating AI-native operating models.
RETAINER
04
THE RECORD
A multi-disciplinary career across hardware, SaaS, IoT, embedded systems, and cloud platforms. Multiple platform shifts: embedded to cloud, cloud to API platforms, platforms to AI.
- ANTARECO-FOUNDER — AI VIDEO & AUDIO INTELLIGENCENOW
- TWILIOAPI PLATFORMS—
- QUALCOMMEMBEDDED & WIRELESS—
- CSRSILICON & CONNECTIVITY—
- STARLEAFVIDEO SAAS—
- BRIGHTSIGNIOT & MEDIA HARDWARE—
This platform shift is the biggest one yet. Most organisations haven’t reckoned with how much bigger.
The conversations that go somewhere usually start with: “We think the way we build products is changing, but we’re not sure what the new model looks like yet.”
LET’S TALK →FIND ME ON LINKEDIN — IF THAT’S WHERE YOU ARE.