Go-to-market
Go-to-market is becoming an engineering discipline
Research, list-building and first drafts are nearly free now. What wins in marketing, sales and business development is judgement, experimentation and the ability to build systems. That changes who gets hired.
A few years ago, "GTM engineer" was not a job title anyone recognised. Today it shows up on hiring plans at start-ups and scale-ups alike: a person who sits between marketing, sales and operations, works with APIs and data, and builds the systems that find, research and reach customers. The title is new. The shift behind it is bigger than one role.
Go-to-market, the umbrella term for marketing, business development, sales, partnerships, customer success and revenue operations, is becoming an engineering discipline. Not because everyone needs to code, but because the work is increasingly about building systems, measuring them honestly and exercising judgement over what they produce.
What changed
Three things happened at once. Data about companies and buyers became easier to access through APIs and enrichment providers. Automation tools made it possible for non-engineers to connect those sources to a CRM. And large language models made research, summarisation and first drafts almost free.
Put together, those changes remove the old bottleneck. A single person with a good workflow can now research hundreds of accounts, find the ones showing buying signals and draft a relevant first message for each. Volume is no longer hard. Which means volume is no longer an advantage.
When everyone can send ten thousand personalised emails, the edge moves to knowing which fifty to send, and what to say.
The new GTM skill stack
The fundamentals have not gone anywhere. They matter more, because everything built on top of them is amplified. But the stack of skills that separates strong GTM professionals now looks like this:
- Strategy and positioning. Knowing who the ideal customer is, what alternatives they have and why they would switch. No workflow fixes a bad answer here.
- Experimentation. Designing tests with enough statistical power, reading them without fooling yourself and understanding when attribution is misleading.
- Data fluency. Enough SQL to answer your own questions about funnels, cohorts and pipeline, without waiting in a queue for an analyst.
- Systems and automation. Connecting signals, enrichment, CRM and outreach so they run reliably, with clean data.
- AI evaluation. Knowing when AI-generated research or copy is good, when it is confidently wrong and how to check at scale.
- Judgement and trust. Deciding what not to automate, respecting consent and deliverability, and protecting the brand.
The risk: automated noise
There is a bad version of this future, and every inbox already shows it: generic outreach dressed up with a line scraped from a LinkedIn profile, sent at a volume that burns domains and goodwill. It is cheap to produce and easy to ignore, and it trains buyers to ignore everyone else too.
Compliance is part of this. India's Digital Personal Data Protection Act, 2023, the TRAI rules on commercial communication, and GDPR and CAN-SPAM for global outreach all shape what responsible GTM looks like. The professionals who understand these rules, and design systems that respect them, will be trusted with bigger budgets.
What it means for GTM careers in India
Many of the most interesting GTM roles in India now serve global markets: Indian SaaS companies selling to the US and Europe, and global companies building revenue teams here. Those roles reward people who combine strong communication with the systems and data skills above. A business development manager who can build their own account research workflow, or a marketer who can design a geo-lift test, is worth considerably more than one who cannot.
How this shaped our Go-To-Market Fellowship
This is why our Go-To-Market Fellowship is built the way it is. It starts with strategy, positioning and pricing, because that is where most GTM failures begin. It spends three weeks on growth and experimentation, including causal inference, and three on business development and enterprise sales. Then it spends four weeks on AI-native GTM: SQL, CRM architecture, automation, AI agents with human review, and machine learning for lead scoring and churn, with compliance throughout.
It is for marketers, BD managers and sellers, freshers and experienced alike, and it runs part-time so you can keep working while you do it. Cohort 03 starts on 26 October.
