I'm a GTM Engineer, I help B2B companies build GTM systems.

I work across three layers of go-to-market:

1. GTM systems: internal AI agents and workflows that power the sales, marketing and customer support teams.
2. Outbound systems: finding the right customers and reaching out to them.
3. RevOps: CRM administration and integration.

I take the manual work a revenue team does every day and turn it into systems that run on their own.

Internal systems that take repeatable manual work off the GTM team, so they spend their time on customers instead of admin.

• For sales. Reps walk into every call already knowing who they're talking to. Prospect research and account briefs are ready before the meeting, follow-ups are drafted, the CRM updates itself, and the best leads rise to the top of the list.
• For marketing. Campaigns go out faster and every lead lands with the right person. New leads are captured, enriched, scored and routed automatically, and campaign results are reported without building spreadsheets by hand.
• For customer support. The team answers faster with the full customer picture in one place. Tickets are sorted and routed, conversations are summarised, and signs of churn or upsell are flagged and handed to sales.

• Signals. Track signals that show an account is ready to buy.
• Enrichment and list building. Build target accounts, decision makers and verified contact details.
• Segmenting. Group accounts by ICP, industry and look-alikes of a company's best customers.
• Messaging and copywriting. Short, plain messages written for each segment, with one clear ask.
• Sending and deliverability. Set up the sending infrastructure and keep deliverability healthy across email and LinkedIn.

• CRM administration. Set up and run Salesforce and HubSpot so the data stays clean and reps trust it.
• Integration. Connect the GTM tools to the CRM, so enrichment, research and outbound activity flow in automatically, with no copy and paste.

1. Map the process. Find the manual steps and where the team loses time.
2. Build the system. Connect the tools, data and AI agents end to end.
3. Ship it live. Deploy it so the team uses it, then measure the results.
4. Plan for what breaks. Check limits, costs and failure points up front, so the system holds up on the hard days.

Clay · Claude Code · Claude API · Codex · Grok · Apify · HubSpot · Salesforce · Python · SQL · Supabase · SmartReach · HeyReach · Vercel · GitHub, and more.

GTM systems (sales) + RevOps

Paste a LinkedIn URL and get the prospect's profile, verified email, an AI-written summary and outreach angle, and a verdict on whether the account fits Anaconda: does the company use AI, and does it run on one of Anaconda's partner platforms (AWS, Azure, Google Cloud, Oracle, Databricks, Snowflake)? One click saves it all to HubSpot.

Built with Clay, Claude, BuiltWith, TheirStack, HubSpot and Vercel.

Outbound systems (signals + list building)

Four custom Apify actors that turn job boards into clean, deduplicated hiring-signal datasets for Clay. Three collect the signals from Y Combinator's job board, jobs.mkt1.co and GoFractional, including founder LinkedIn profiles and the original ATS apply links. The fourth checks each LinkedIn posting is still open and whether it's remote, hybrid or on-site, before anything reaches outreach.

Built with Python, JavaScript, Apify, Crawlee, Playwright and Clay.

• Email: aishataliyu364@gmail.com
• LinkedIn: linkedin.com/in/aisha-aliyu