The GTM playbook has changed more in the past two years than in the decade before.

I've spent 15 years helping B2B companies hone their GTM and pricing strategy. And I'm still coming across new terms almost daily: AEO, context engineering, MCP, FDE, token economics — the list keeps growing. Sometimes staying on top of the latest GTM jargon feels like a hazing ritual that should’ve been banned in the 90s.

But these aren't just vocabulary updates. Each one signals a real shift in how B2B companies acquire and expand customers.

This field guide breaks down the must-know terms and levers that define the modern GTM playbook in 2026. It covers the key motions and channels, the AI GTM infrastructure teams are building, the signals driving smarter outbound, and the pricing models that are actually working. It's written for founders and GTM executives who want a crash course of what’s important for their strategy.

Choosing your GTM motion(s) and channels is step one. Focus on one primary GTM motion at a time — it’s nearly impossible to get great at multiple simultaneously.

The primary way that a company acquires and expands customers. The six main GTM motions in B2B are:

Inbound is the most popular GTM motion, according to the State of B2B GTM Report that Maja Voje and I published last year. 23% said it’s their primary GTM motion. Product-led was dominant for products that cost less than $5k per year and for early-stage companies with <$1M ARR. Account-based was most popular for expensive products (>$25k average ACV).

No single motion correlates with better growth rates — the right choice depends on ACV, stage, and product type. While each motion still works, I’m most bullish on account-based GTM as an antidote to spray-and-pray.

Read more: How to build your GTM strategy from scratch

An account-based GTM strategy targets specific named accounts with coordinated marketing and sales effort instead of broad-based demand generation.

This is often shortened to ABM (account-based marketing), although that tends to get pigeon-holed as targeted digital ads via platforms like 6sense, Demandbase, Terminus, RollWorks, Metadata, or Primer (part of Unhinged Perks).

As AI makes generic outreach cheap and ubiquitous, differentiation comes from precision, relevance, and deep context around a small set of high-value accounts. At the same time, AI has collapsed the cost and manual effort required to run ABM. I think account-based GTM will be increasingly popular, particularly for B2B teams with $50k+ ACV and an addressable market under 20,000 companies.

Read more: How to build a modern ABM engine

Product-led growth (PLG) is a GTM model where the product is the primary driver of acquisition, activation, and expansion. This was already on the rise among SaaS products like Slack, Dropbox, and Atlassian. AI-native products are taking it a step further.

They’re releasing ungated products where new users can simply get started from the homepage, no signup required. They’re building ‘headless’ PLG experiences for AI agents rather than human users. They’re using AI to vibe code free sidecar products, standalone micro-tools that exist as an on-ramp to the core product. And they’re dramatically accelerating growth experimentation — Fyxer ran 514 growth experiments in the past 12 months.

While PLG or self-service is a great starting point, teams almost always layer in sales teams (as I covered in my AI-native org report). Product-led sales (PLS) is a bridge between PLG and sales. It uses product usage signals, called product-qualified leads (PQLs), to trigger sales outreach at the right moment.

An emerging PLS trend is de-anonymizing personal email addresses. AI-native products see about 75-90% of signups are personal emails; de-anonymizing these has gotten much more accurate and less expensive than before.

Read more: PLG resources in Growth Unhinged

Executing your GTM motion requires betting on channels to cost effectively reach the right target customers. The average software company says they have 5 core GTM channels and another 5.5 GTM channel experiments. It’s no wonder we all feel exhausted.

As of October 2025, the most common GTM channels were LinkedIn (66% adoption), SEO (53%), and warm outbound (48%). The most common channel experiments were intent-based outbound (49%), AI discovery aka AEO (47%), and large conferences (43%).

The single best channel in terms of likelihood of having an impact surprised me: intimate events. As Emily Kramer from MKT1 recently wrote, “Dinners are the new trade shows.”

Warm outbound and intent-based outbound had surprisingly positive spots, too, proving that outbound isn’t over (except for bad outbound perhaps).

Looking ahead, the top three areas where teams are increasing GTM investments the most include AI discovery or AEO, intent-based outbound, and LinkedIn (via in-house or external creators). Ecosystem marketing and splashy product launches are other ‘next big thing’ channels that are under-leveraged relative to their impact.

Read more: The State of B2B GTM Report

AEO involves optimizing content, brand mentions, and offsite presence to appear in AI-generated answers from ChatGPT, Claude, Google AI Overviews, and more. AI searches probably represent at least one-third of all searches these days after accounting for Google AI Overviews. This is now the #1 growth channel where B2B marketers are increasing investment.

Why this matters: AI responses recommend products rather than simply provide a list of links. This means buyers might generate a shortlist of products (or even make a buying decision) before ever visiting a vendor’s website.

AEO is notoriously hard to measure because AI engines don’t send much referral traffic, and instead keep users within their walled gardens. Marketers are instead measuring: (a) share-of-voice in AI queries, (b) LLM sentiment, i.e. how AI engines describe the product relative to competitors, and (c) pipeline influence attributed to AI engines.

Read more: What’s working right now in AI search

Signals are indicators of buying intent, ideally among prospects that fit your ICP criteria. These could be first-party signals (ex: product usage, website visits), second-party signals (ex: attend a partner event), or third-party signals (ex: job changes, funding rounds, competitor engagement, search behavior).

Signal-based outreach uses this data to time and personalize outreach. When asked which GTM channels B2B companies are investing the most into for 2026, intent-based outbound was #2 on the list.

Early adopters use signals to run AI-native GTM plays like closed-lost deal re-engagement, micro-campaigns (outbound campaigns aimed at highly-targeted lists of 50-250 contacts), and competitor displacement campaigns.

Read more: The best AI-native GTM plays you’re not running

Marketing through and alongside partner networks — co-marketing, shared distribution, marketplace presence, and leveraging partner audiences — rather than relying solely on owned channels.

This is core to a partner GTM motion, but is an increasingly important growth channel regardless of GTM motion as Emily Kramer recently unpacked in Lenny’s Newsletter.

Read more: Ecosystem is the next big growth channel (Emily Kramer)

A founder, employee, or external voice who builds a public audience through content (newsletter, LinkedIn, podcast, YouTube) as a growth channel.

As I’ve written about before, original storytelling has become a hot GTM skill. Companies also partner with external creators, aka influencers (although that term is no longer in fashion), through sponsorships, affiliates, and co-created content. 13% of GTM teams now say B2B creators are a core channel while 42% say it’s an experiment.

The biggest challenge is that B2B creators have been notoriously tricky to scale. This is changing as B2B creators attract larger audiences and as platforms emerge to help manage creator programs (see: Passionfruit, Limelight, Favikon). Relevance beats reach: a nano-creator with 2,000 followers in your ICP will often outperform a generalist. I’d also recommend deeper, longer-term partnerships with the top creators in your space.

Read more: Should influencers be part of your GTM strategy? (Maja Voje)

FDEs are technical experts who embed directly with customers to implement, customize, and optimize a product in their environment — blurring the line between sales engineer, solutions consultant, and product team. The role has exploded recently: Adam Schoenfeld found that 39% of top AI companies are actively hiring for forward-deployed roles at $213k-$370k+ in comp.

The model is now expanding beyond engineers. Many companies now run forward-deployed PMs, data scientists, and domain experts alongside engineers. Adam calls this FDX — forward-deployed everything.

Read more: Forward-deployed everything (Adam Schoenfeld)