3 Ways Startups Should Be Using Generative AI Right Now

Generative AI is helping startups make massive productivity gains through improving Sales and Marketing, Internal Operations and Product. Startup founders have to be able to sift through the hype to make Generative AI a competitive advantage instead of a distraction. Here are our best tips, gathered from dozens of interviews with startup CEOs’ experiences. 

1. Sales and Marketing

Generative AI can create vast amounts of content quickly on a wide range of topics. You can use Generative AI to get your Sales and Marketing team get started and overcome writer’s block, for example, to:

• inspire blog post topics on your SEO keywords
• write a first draft of an outbound email sequence
• summarize a prospect’s profile and use case from call notes

However, you’ll want to refrain from copying the exact text ChatGPT generates into your marketing blog, since search engines are getting better at detecting and dinging AI-generated content and spam. Instead, consider using phrases for inspiration, adding your brand’s own tone and including examples that are specific and relevant to your audience. 

2. Internal Operations

These days, operational efficiency and a path to profitability are top of mind for startups and investors alike. Generative AI can make a huge dent in assisting, for example:

• engineers to auto-generate code, especially tests and boilerplate, like OpenAI’s Codex and Github Copilot 
• data analysts to generate, fix and optimize SQL from natural language on your own data schema. You can read more about best-in-class AI SQL Copilots here
• operations managers to proactively flag anomalies like unusual spikes or dips in activity with customers, order volumes, API calls etc.

However, for now, you’ll want to have a human check any code or SQL that’s generated to ensure safety, explainability and accuracy on your specific business logic, and beware of tools that promise a fully automated solution that you cannot verify. 

3. Product

CEOs and product managers are possibly most excited for engineers to use LLM APIs from providers like OpenAI, Anthropic and libraries like LangChain, for example, to improve:

• self-serve activations by enabling users to create content on your platform easily, e.g. how Zapier lets you describe your workflow and auto-generates a Zap for you
• customer satisfaction and retention through auto-summarization and better search, e.g. how Notion lets you summarize text by highlighting it
• strategic decision-making by consolidating insights across product analytics and user interviews notes

However, you’ll want to make sure to instrument and alert on user behavior to see if features are actually being used, not being used to spam other users or generate malicious content, or actively hurting your product’s reliability. When selecting a LLM API provider or language framework, you’ll want to make sure they provide you with enough governance, testing, rollback and privacy features to protect your users, and make fast updates as your business needs evolve.

Overall, Generative AI can help startups remain nimble by 10x-ing productivity of resources while providing a super user experience, if done right. If you want to follow how other startups are improving business efficiency with automated data alerts and actions without spending their most precious engineering resources, check out some case studies or try LogicLoop for free!