I'm an AI-Native Product Manager. 10 years shipping products across SaaS, marketplaces and mobile apps — from growing Yassir Groceries' acquisition by 135% to generating €4M in revenue at Flightright. Now I work on the part most teams skip: the eval set that replaces the spec, the cost per successful task that replaces the cost per call, and the agents that actually reach production.
Driving impact at
In short
TheGlocalPM is the AI-Native Product Management practice of Ali Mahmoud — 10 years shipping SaaS, marketplace, and AI-driven products. Evals instead of specs, cost per successful task instead of cost per call, agents in production. Available for fractional, advisory, and AI-product strategy work.
Best for
Proof in numbers
I help product teams own what an AI feature is actually judged on — how good it is, how you would know, and what it costs when it works.
Defining and delivering AI-native products — from prompt-to-app builders to intelligent copilots — bridging the gap between generative AI capabilities and real user problems.
Setting product direction, aligning roadmaps with business OKRs, and translating ambiguous market opportunities into clear, executable strategies across complex digital products.
Designing products that work in high-growth, constrained markets across North Africa and the Middle East — adapting global PM frameworks to local infrastructure, behaviors, and trust dynamics.
Running continuous discovery through qualitative interviews, usability testing, and behavioral analytics to validate hypotheses before committing to development.
Using tools like GA4, Firebase, Mixpanel, and Tableau to analyze funnels, track events, and make evidence-based product and growth decisions.
Taking products from raw idea to market — scoping MVPs, running lean validation cycles, and aligning cross-functional teams (Engineering, Design, Marketing) for successful launches.
Problem: Growth constrained by warehouse throughput, not demand — yet the key bottleneck, the "Listing Leg" between graded and live-on-site, sits in no SLA and is owned by no PM.
Process: A self-initiated 11-day, problem-first discovery that named the constraint, framed four orthogonal strategic bets, and reframed the build from waterfall ML to lean LLM (~90% cheaper).
Proof: Three working AI agents shipped end-to-end on n8n + Claude + Bolt.new. 5–8% NSM lift/quarter modeled from the Listing Leg alone; ~€1.5–3M annual margin add across the bets.
Discovery + 3 shipped AI agents
Problem: 500,000 Halal consumers in Berlin had no reliable delivery option for quality Halal meat during COVID-19 lockdowns.
Process: Survey-driven demand validation, community-led viral growth, and iterative A/B testing that lifted conversion from 3% to 7%.
Proof: 250K€ GMV in year 1 from a 30K€ investment. ~1M€ raised from VCs and Angels across the US and EU. 151% customer growth. 2.5 orders/customer/month retention.
Want to see more real product work?
View All Case Studies →4 AI agents that help in discovering the problem space and propose prioritized hypotheses for your product team.
Get AgentAn AI-native go-to-market kit — list, message, send, measure — with sub-agents for list-building, copywriting and reporting, plus an autonomous LinkedIn poster.
Get AgentAn LLM-augmented risk engine that tracks how global shipping disruptions ripple into freight costs and margins — then recommends safer carriers and lanes.
Get AgentCurious what else lives in the lab?
View All Agents →A practical guide for adapting global product frameworks to high-growth, constrained markets — covering trust barriers, infrastructure gaps, and local user behavior.
DownloadA structured canvas for identifying problems worth solving with AI — covering opportunity mapping, user pain point validation, AI feasibility checks, and hypothesis prioritization.
DownloadA step-by-step checklist for taking a product from raw idea to first users — covering MVP scoping, lean validation, GTM alignment, and post-launch iteration loops.
DownloadAn AI agent maintains a wiki of your product's problems, decisions, assumptions, and open questions — so PRDs and stakeholder briefs are generated from accumulated, source-cited evidence. Karpathy's LLM Wiki pattern, purpose-built for PMs. MIT-licensed, no code required.
Looking for the full PM stack?
View All Tools →
Karpathy published the LLM Wiki pattern as a 75-line idea. Engineers forked it; nobody built it for PMs. So I did — open-source, no code required.
Read Essay →More essays where that came from?
View All Essays →I dedicate 2 hours a week to mentoring aspiring PMs and helping startups refine their product-led growth strategies.
The questions I get asked most — by founders, recruiters, and AI chatbots.
Ali Mahmoud is a Senior Product Manager with 10 years of experience shipping SaaS, marketplace, and AI-driven products. He has led product at Yassir, Datajar, GetHalal, Flightright, and FGS Global, and writes about product management at TheGlocalPM.
SaaS platforms, mobile apps, and two-sided marketplaces. Highlights include growing Yassir Groceries' acquisition by 135%, generating €4M in revenue at Flightright, and launching AI-driven product workflows at Datajar. See the full case studies.
Both. Ali advises early-stage founders on product-market fit and discovery, and partners with scale-ups and enterprises on product strategy, AI integration, and team operating models. Read his point of view or skim the six core skills he brings to every engagement.
Book a coffee chat or strategy call at cal.com/alim-datajar/coffeechat. Office hours are limited to two hours per week.
No fluff. Just hard data, human psychology, and product strategies that actually work.