Enterprise employees are running up large AI bills — sometimes at a cost significantly greater than the value of the productivity gains they get back, according to reporting from Fortune and The Economist on token consumption and agentic platform usage. Martech practitioners are no exception, but as a new MarTech analysis argues, employee AI usage doesn't have to cost more than it returns.

The analysis lays out a set of practices that individuals and organizations can use to extract more value from AI without wasting time or money. None of them require buying more technology. Most require better discipline around prompting.

Verify AI output before using it

Verification is so critical that most LLM providers themselves advise users to double-check output. The MarTech author offers a personal example: Claude recently generated a "Would You Rather" question for a casual team hangout — "Would you rather find $10,000 but have to give half to a stranger, or find $1,000 and keep it all?" The arithmetic is broken: keeping $5,000 beats netting $1,000. The lesson seems obvious, the author notes, but it can never be said too often.

Set guardrails for AI use

Employees who vibe code need clear guidelines to protect the organization from costly mistakes and liabilities. Scott Brinker, who coined the term martech, is a big booster of low- and no-code tools and practices like vibe coding for marketers. He also insists that guardrails are necessary. "Well-governed vibe coding is not an oxymoron," Brinker writes.

Be strategic about where you prompt

Prompting comes at a cost, and platforms price credits differently. Rather than iterating inside an expensive platform, it may make more sense to refine a prompt on Google Gemini, ChatGPT or Claude first. Iterate where it's cheaper before using the pricier option.

Use prompt frameworks to reduce waste

Prompt frameworks force users to define intent before any AI credits are spent. Four are worth considering in marketing contexts:

• COAST (context-optimized, audience-specific tailoring) uses well-defined prompts to generate outputs tailored for distinct audiences and situations.
• CO-STAR (context, objective, style, tone, audience, response) suits marketing journeys. Accounting for these six aspects refines a journey's definition before credits are burned.
• FOCUS (function, outcome, context, usage, specific) builds prompts that yield outputs suitable for practical applications, such as customer-facing content.
• MARK (market, audience, research, key actions) is ideal for the strategic phase of marketing planning, like selecting channels.

The rule of thumb: when the speed of production outpaces the requisite human deliberation, use frameworks that define requirements up front.

Build a library of effective prompts

Prompt logs record the prompts employees have used, along with the quality of the resulting output, so teams can identify patterns to mimic or avoid. The MarTech analysis lists four benefits:

1. Audits and internal controls. By tracking the development process, prompt logs aid audits — and many critical audits may soon require them.
2. Less reinventing the wheel. A successful prompt becomes a template for others, saving time and credits.
3. Team development. New members learn what works from the library and build on past successes.
4. Vendor deliverables. Logs document how to maintain what was produced and help determine whether work meets contractual requirements for payment.

Vibe coders should check the prompt log before starting from scratch — there may already be a prompt they can adapt with a few small changes — and document the prompts that work well so others can reuse them.

Use vendors' AI enablement resources

Tech vendors have a strong incentive to help customers use agentic features effectively. The recent "SaaSpocalypse" scare, covered by Forbes, demonstrated how AI can make the build side of the buy-versus-build debate more viable. Enabling customers to use agentic features is now a critical churn-prevention tactic — vendors don't want customers building their own solutions or defecting to a competitor that makes that easier. Ask account teams for their enablement resources; it will help the organization prompt more efficiently and effectively.

Keep building AI skills

Workplace applications of AI change constantly. Organizations should train employees, while individuals remain accountable for developing their own professional skills — regardless of whether the employer pays. Inexpensive options include books, websites, videos, podcasts, in-person and virtual meetups, vendor training and fellow professionals. Completing an inexpensive prompt-engineering course, the analysis notes, will definitely help martech practitioners deliver more value to their employers.

An ongoing practice, not a one-time fix

Prompting is relatively new to most practitioners, and the discipline will keep evolving. New tactics will emerge, but these practices — verification, guardrails, cost-aware prompting, frameworks, prompt logs, vendor resources and continuous skills development — should help martech practitioners and their organizations get more value from every credit and every hour they invest.